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How to know your customer using data

With more customer data available than ever before, teams can finally identify critical trends quickly and make smart pivots for faster growth. Learn how to apply these strategies during COVID in this blog.

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Screen Shot 2020-09-03 at 10.32.35 AM

Unlocking NetSuite Data with Incorta for IT/Analytics

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Phil Reinhart: Hello everybody Hello Hello Hello welcome welcome welcome.

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Phil Reinhart: we're going to let everyone trip plan a little bit here, and then we will go ahead and get started in a minute or two while everybody gets a situated with their video and their audio and everything.

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Phil Reinhart: As always, I do have a couple jokes.

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Phil Reinhart: they're not great.

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Phil Reinhart: I kind of laugh at myself it's actually kind of cringe worthy matter of fact, but we're gonna say and tell them anyways because we all want to hear them.

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Phil Reinhart: um so here's the first one it's quite short and it's really bad who's the father of data.

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Brian Keare: No, no phil who.

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data.

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Ethan Post: I gotta be honest that that actually might be the best one which is probably what.

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Ethan Post: A compliment that you think.

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Phil Reinhart: No, I didn't even really try come on all right here's no there's no.

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Phil Reinhart: I collected, a lot of data, trying to disprove disprove confirmation bias, the results were exactly what I expected.

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Phil Reinhart: Alright, well, let that one just see been maybe you're gonna laugh like in an.

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Brian Keare: hour that work.

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Brian Keare: That work.

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Brian Keare: I got it awesome.

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Phil Reinhart: Thank you well, those are the two I have for today.

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Brian Keare: Confirmation bias i'll.

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Phil Reinhart: Try to work in a couple more as we go.

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Phil Reinhart: Through but anyways hi everybody, welcome to our webinar today in quarter, for it analytics my name is spelt reinhardt I am the i'm a sales guy here in quarter and i'll be your moderator for today.

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Phil Reinhart: Just some quick high level call to actions that I just are actually before we get into that housekeeping before we begin.

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Phil Reinhart: If you have any questions during the presentation, please type them into the Q amp a box and anytime you can reach out to me directly in the in the chat box as well if you don't want it to be public.

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Phil Reinhart: i'll reach out to all of you can make comments funny jokes whatever you can make fun of me, whatever you want just you know, we want to hear from you and.

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Phil Reinhart: Also, you know if you want to reach out to us afterwards you've got our names, you can find us on linkedin we are you know definitely open to communicating and we'd love to meet and and talk about you know what's on your mind and and where you see data going today.

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Phil Reinhart: So some call to actions in the agenda, we we really want to point out that here, in October and really all Q4 we have this program called a value sprint.

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Phil Reinhart: And what this value sprint really allows you to do it, it gives you our time our talent and our technology to be able to solve up to two use cases and not only we.

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Phil Reinhart: Just you know, not only are we showing you how important works, but we're actually proving out and getting outcomes, so we want to, we want to find a problem in your business where you see their.

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Phil Reinhart: pop in May may be opportunity for top line dollar impact or a process improvement, maybe some fit savings and cost containment.

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Phil Reinhart: Wherever you see that opportunity we want to team up with you give you, you know teach you how to fish but also go out and solve those problems and realize those you know with your business partners.

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Phil Reinhart: Over that value sprint so that's definitely you know, the call to action after this webinar we also have all of the sessions that we've done throughout this entire series recorded, so those will all be available to you.

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Phil Reinhart: And will be will send it out we'll be sending it out via email, so that you have easy access but definitely reach out to us about the value sprint.

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Phil Reinhart: So now i'd like to introduce our speakers today, so you know as always we've got Brian here and ethan Brian he's our CIO here in quarter, he was the CIO over at Norton security and actually launched.

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Phil Reinhart: In court to their he almost made and what we call it in an ocean moment that turned into an Aha moment, where he was about to spend millions of dollars.

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Phil Reinhart: On their data strategy in a different direction and chose to go within core data and it saved them.

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Phil Reinhart: During the tariffs last year, the big tear of changes that affected the nor tech business and then he ultimately decided to join in courts that because.

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Phil Reinhart: of how much it revolutionized his perspective on data so that's Brian and then we also even he's the head of courses pre sales Center enablement here.

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Phil Reinhart: he's got three years of experience here in courts and he's going to career of implementing different systems across beyond analytics because he's got a very broad perspective.

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Phil Reinhart: In your world that he can really bring to to the call today so that's who's talking, today, and so without further ado i'll hand it over to Brian to kick us off and ethan's gonna gonna run slides for us, thank you.

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Brian Keare: Great thanks so much phil really appreciate it i'm coming in audio only today, because I am the unfortunate.

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Brian Keare: Unfortunately, am reliant on spectrum business for Internet here in Los Angeles, and it looks like spectrum is having huge problem in Los Angeles and across the country.

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Brian Keare: So So hopefully this will come through if not i've got my team mates to jump in and help out, so what we're going to talk about today is in quarter, for it and analytics.

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Brian Keare: But let's take a quick step back and give you context, some of you who have participated in our previous webinars over the past few weeks, and thank you for joining.

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Brian Keare: Have gotten a little bit of this context, but I think it's important to re establish it just before we jump into some of the finer points that that it cares about and with respect to advanced analytics.

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Brian Keare: So as phil said before I came to encarta I was, I was CIO Iran business systems and data analytics that North tech nore tech is a global manufacturer of smart products for small businesses and for homes and we had pretty complicated, we had a pretty complicated ecosystem that covered.

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Brian Keare: You know, multiple continents countries currencies thousands of employees dozens of locations.

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Brian Keare: How did we run nor tech well at the Center of how we ran it was indeed netsuite we found netsuite to be.

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Brian Keare: An extremely capable system that allowed us to manage our global business in multiple currencies and I think we were pretty great at.

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Brian Keare: At using netsuite to power, our global business, so we would build dashboards that would give us a bird's eye view of what was going on here is an example of that.

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Brian Keare: But I think is, those of you who are familiar with netsuite know once you get into.

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Brian Keare: netsuite and trying to manage business you quickly find yourself navigating from page to page and so next slide talks about an example, if I have a KPI and I want to drill down from a KPI into something my view my browser switches and all of a sudden, I go to a individual report.

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Brian Keare: So many of us if we're very adept at doing this, we will do this constantly and we might end up having 75 different tabs open that reflect dashboards plus reports are saved searches.

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Brian Keare: As we get more sophisticated in how we leverage the tools that are available to us in netsuite we might create a safe search that we then put on on our main dashboard.

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Brian Keare: So here's An example of this, where i've got to save search and different folks throughout you know the hundreds, thousands of people in our company would have different dashboards that they wouldn't manage their day with.

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Brian Keare: And they would have you know, in this case open purchase orders in other cases, it would be managing supply chain, from the it perspective, it would be.

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Brian Keare: How is the system going how well are we processing transactions and so that would be an example of how we would do it, but again once you get into a saved searches, we all know.

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Brian Keare: What can you do from there well you click on something, and you can view one transaction at a time.

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Brian Keare: So life inside of netsuite is a lot of individual browser windows one transaction at a time and managing one save search at a time, which represents rows and columns of data inside of netsuite.

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Brian Keare: A lot of times, we find that when we're doing this that that isn't good enough, and so what do we do we take the results of saved searches and we throw them into excel and XL.

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Brian Keare: We believe ends up being empowering for us because I can throw multiple saved searches in there, I could start to add.

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Brian Keare: formulas and do a little bit of analytics inside of excel in ways that are eaten may be easier or more familiar for us to do, then inside of netsuite and we have excel in addition to things inside of netsuite that we manage our business with at nor tech.

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Brian Keare: Our you know biggest excel spreadsheets would be pretty darn big hundred 64 megabytes.

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Brian Keare: encompassing dozens and dozens of worksheets and we would download save searches and manage that whole process.

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Brian Keare: So sometimes that gets unwieldy and you can see how, when we'll, be it is from the next slide that describes our business system ecosystem.

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Brian Keare: At nor tech, and you can see, although we manage our business in netsuite we would have to bring in data from acquisitions that were on companies run.

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Brian Keare: In er piece that might not have been netsuite and so, while we were waiting to integrate them into netsuite we would need to report on them, we had supply chain, we talked about that last time.

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Brian Keare: We had distribution wns three PL systems customer facing systems all sorts of systems so as we think about how we can report on data outside of netsuite we brought a lot of that data into netsuite.

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Brian Keare: Using tools like Dell boomy but eventually you say hey i've got a bunch of data let's try putting it in a data warehouse to consolidate how we.

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Brian Keare: Report on it, so you, you know what's the normal process for doing, creating a data warehouse you create your retail tools you throw it into a data warehouse.

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Brian Keare: You get it ready for reporting and in either excel or power bi or tablo in order to do that, you can't just stop at the data warehouse you actually need to model it.

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Brian Keare: Create views and cubes that power effectively your visualizations that ends up not being good enough and so i've talked about my story, where we had our Aha moment and still talked about where instead of this process, which was pretty brutal and which would break.

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Brian Keare: We found in quarter incorporated really did turn out to be a connected go alternative the team at nortel figured that out over a weekend to prove the value.

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Brian Keare: Of in quarter what's the value, I think the next slide sums up what the core value of in quarter is in three easy steps number one you connect your various data sources, including netsuite to in quarter.

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Brian Keare: You don't have to reshape it you don't have to do atl you bring it in exactly as it is and ethan will show us some of that today.

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Brian Keare: And once it's inside in court, a part of our secret sauce is understanding how that data fits together we just pointed at each other, we don't need to write complex sequel we don't need to reshape it we don't need to flatten it via.

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Brian Keare: We don't need to flatten it we don't need to prepare it for cubes and we can start performing modern bi using the built in visualization tools that in court, a house.

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Brian Keare: So, from a business perspective, the three ha's really are that, in addition to getting summary aggregation.

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Brian Keare: You are able to drill down to row level transactional detail and you're able to flip back and forth, why is this important well it's important because.

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Brian Keare: you're not fighting over how somebody's got to those summary level metrics summary level calculations, because you can see, really quickly and validate how those are built up with individual transactions.

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Brian Keare: The second thing is that it's a single source of truth, you know that in court, a matches the source system, because there is no reshaping of the data, the data that's in court is exact replica of what's in the source system and so it's really easy to validate CFO is love this.

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Brian Keare: And CFO love this because you have a single source of truth third thing is that you got a possibility for true self service, because you know, and this is beginning to get to the point of where it really cares.

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Brian Keare: They can empower an analyst who could inside of netsuite create a safe search, they can empower them to do modern complex sophisticated bi dashboard.

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Brian Keare: on their own, and you can give your supply chain department, the list of 100 fields that they might be interested in to throw on a dashboard and to start doing modern.

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Brian Keare: analytics you can give finance a different set of fields that they might care about, and you can really empower your team.

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Brian Keare: To really achieve self service, and that is a huge difference compared to what is the alternative, which is that they're knocking on your door asking you for data asking you to create a power bi report asking you for something that is on your backlog.

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Brian Keare: And we all know what that backlog looks like it's really hard to keep up and if you can change the game and empower your teammates.

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Brian Keare: To do it on their own to fish for themselves, it really changes the whole nature of the game so that's the Aha for business, I think there's probably a triple Aha for it, and this is really starting to get into the meat of what we're going to go into today number one.

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Brian Keare: We we provide a lot of intelligence out of the box we're going to show the blueprints and with respect to netsuite which brings in.

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Brian Keare: Standard tables and standard fields, but if, but we all customize the heck out of our source systems netsuite is no different in fact netsuite.

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Brian Keare: is more flexible than most in its ability to add custom fields and custom tables those become really important as dimensions to be able to report on.

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Brian Keare: In traditional data analytic systems getting new fields and new tables into your data warehouse and reportable is often a very cumbersome process in that suite.

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Brian Keare: It can be as easy as a couple of minutes to light up that and ethan's going to show an example of that today so extremely eXtensible and again we are just replicating exactly what is in the source system you add and go.

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Brian Keare: The second thing is that we're going to talk about today is that you can mimic your security of your source system in a really easy way, this is no.

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Brian Keare: This is no straightforward task, as many of you know, and once you get something into a data warehouse, for example, or index out think about excel.

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Brian Keare: And the dumping of data into excel and how all the sudden it becomes really easy to violate what you had set up inside of your source system which might be.

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Brian Keare: That only certain people can see certain types of transactions certain transactions only in certain subsidiaries certain departments certain locations.

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Brian Keare: Managing that once you allow data csv format xml format data warehouse format to go outside of the source system can be a huge headache and, in fact, many of us throw up our hands and say that's actually an impossible task.

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Brian Keare: to accomplish well within quarter it's actually very straightforward to replicate security that you have in your source system and and netsuite is no.

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Brian Keare: Different from how we would treat other systems, makes a huge difference and so ethan will show you a little bit about how we can fashion that you know way that ensures that you can deliver.

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Brian Keare: Flexibility and data analytics to your team, while maintaining data security it's a huge deal and in court, it is as good as any system i've ever seen.

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Brian Keare: at being able to do that in a really straightforward, easy to understand, easy to implement way.

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Brian Keare: The third thing that we're going to talk about is that once you have your data replicated inside of incorporated opens up a world of possibilities of advanced analytics that.

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Brian Keare: are otherwise unavailable or that would require some really expensive solutions to achieve, and you know I think there's two examples of this, that all that came into play for.

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Brian Keare: myself at nor tech all the time number one is creating snapshots of data understanding how.

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Brian Keare: transactions, you know I think two areas would that we would focus on would be understanding transactions and how they changed over time, so it could be.

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Brian Keare: Open sales orders or estimates that we're waiting for approval and we all know that you know as we're negotiating with customers or customers are putting in change orders those can change over time, or as you're waiting for a.

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Brian Keare: An order to be approved the inventory levels that would support, whether or not you could fulfill that sales order might change over time so understanding.

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Brian Keare: How those the picture of those sales orders changes over time is something that's pretty hard to.

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Brian Keare: pretty hard to do really easy to do inside of encarta same thing with inventory snapshots what was my inventory level of widget X.

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Brian Keare: Three weeks ago, two weeks ago, yesterday, a year ago, we can snapshot that really easily in in court and give you.

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Brian Keare: You know, let you time travel and take a look at what that was over time it's really a game changer analytics was.

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Brian Keare: The second thing is everyone's really talking about predictive analytics ml and Ai and there's a ton of opportunities around that so.

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Brian Keare: If we go through the next slides i'll just kind of set up ethan's ethan's DEMO by giving you a quick picture of.

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Brian Keare: What it looks like what some of these things look like inside of netsuite, for example, and then how we deal with them inside of how we deal with them inside of.

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Brian Keare: In quarter so netsuite you know how do you customize here's an example of you want to add some some.

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Brian Keare: custom fields that go on top of your item master this is very familiar to any of you who have customized your netsuite environment.

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Brian Keare: What do we do inside of in quarter, well, we give you a very easy to view dashboard across all dimensions, this is the items dashboard it tells you every single field that is in your environment on the item table, whether or not it's a standard netsuite field or custom field.

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Brian Keare: And whether it's currently President in quarter or not, and whether it's actually linked to a different kinds of table, so we give all of that intelligence.

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Brian Keare: To you, to make it super simple to then add a field and additional field inside of in quarter next slide shows that once you are inside and quarter in you want to take a look at something as simple as the item table, yes, you can see the exact match of what you see inside of netsuite.

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Brian Keare: inside of the quarter you add it a couple minutes later you're ready to go and report on it.

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Brian Keare: So the next use case talking about permissions and security, the example that we're going to show is related to.

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Brian Keare: You know, here is a customer and you know a lot of times we've you know many, many companies will have.

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Brian Keare: Customers that are managed by sales REP that's the general way we do things right so some companies care about taking a look at transactions and segregating transactions by sales REP, that is to say.

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Brian Keare: If you're a sales REP and part of the sales organization, maybe you only get to see.

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Brian Keare: transactions that are related to customers that, for whom you are the sales REP and you don't get to see transactions for other customers so that's a use case that.

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Brian Keare: is typical other use cases that are typical relate to limiting the scope of what you see by subsidiary by department by location, all of the different things that you will see in.

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Brian Keare: netsuite roles and permissions and so we'll go through an example of that and finally there's an example of a simple sales order inside of.

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Brian Keare: Inside of netsuite here's a sales order you know for a certain amount, and you know, maybe you scratch your head or you go around the room and say.

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Brian Keare: hey you know didn't these numbers work these numbers different didn't three m, have you know more open sales orders.

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Brian Keare: Yesterday, then today what in the world happened inside netsuite what do we do we dive down into system notes, and this is the granularity that you get to see you get to see.

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Brian Keare: that yes, Brian wolf changed that sales order and it went down, you know by $1,000 but it doesn't actually give you the granularity that you need to see exactly what happened all you know is that.

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Brian Keare: Yes, indeed it did go down you're right your hunch was right, the numbers went down day over day on that sales order pending approval.

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Brian Keare: But you don't really have the granularity to understand what the snapshot in time looks like So those are the three things that ethan's going to go over.

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Brian Keare: The last thing that I will point out is that you know it's a slide that we talked about previously, which really talks about the value prop of incorporated in terms of time to implement.

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Brian Keare: You know the corollary of what ethan is going to show which is once you have it up and running, that it's really easy to change and modify and add and go.

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Brian Keare: This shows you how easy it is to implement at North tech we implemented in quarter.

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Brian Keare: In the average is one to two months we implemented in one month across the entire enterprise which was a land speed record for any enterprise.

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Brian Keare: system that we ever implemented at nor check and you know the comparable implementation of a data warehouse two point O or another complex system would be significantly longer than that so, whether it be.

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Brian Keare: Standing up a trial and seeing your own data inside of in quarter or actually implementing it our time to value is second to none and.

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Brian Keare: You know I think that's important to take into account ethan will show you some of the power and flexibility here in the DEMO so over to you and ethan thanks so much.

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Ethan Post: yeah thanks Brian I appreciate you taking that up and in such a way and kind of walk into the individual use cases.

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Ethan Post: Almost take a step back before really diving in the weeds because.

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Ethan Post: As phil kind of alluded to, you know i've experienced in post sales and I understand kind of the interplay between the I team analytics organization.

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Ethan Post: And the business users who have their own set of requirements right so sometimes i'll kind of like in the the it team to you know what the business users.

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Ethan Post: assume sometimes it's like a magician right, so you look at this diagram that Brian speaking to right now and realize that.

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Ethan Post: hey we go down this path of a kind of a typical data warehouse we're looking at eight to 24 months.

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Ethan Post: But the entire premises of this is that your technical your analytics your bi teams can kind of presume what the end users are going to want to do with the data right.

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Ethan Post: So reshaping that data in something like a star schema automatically boxes in your end users in terms of the questions they can answer.

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Ethan Post: So when I talk about this DEMO but i'm really going to do is kind of unpacking in a several layers right so layer number one is how quickly, can you get up and running, so if the business things you're a magician.

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Ethan Post: what's the magic behind the quarter to actually give you that kind of speed to insight, but also the ability to stand up in court in a couple of weeks.

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Ethan Post: and start to give them access to their business data with an unlimited number of questions that they can ask right.

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Ethan Post: So let's kind of unpack that for a second, and this is, you know fairly fairly basic in terms of what encoded does and we've kind of talked through this and each of the sessions that we've had so far, but as I log into this encoder instance.

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Ethan Post: What you're going to see right off the BAT here after I close out a few of these windows, is this concept of a netsuite blueprint.

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Ethan Post: So the beauty of the netsuite blueprint for a quarter, is the fact that it comes pre packaged with a set of dashboards and reporting content right.

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Ethan Post: Supporting things like executive reporting finance sales order management operations and so on and so forth.

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Ethan Post: It also comes with this middle tier business schema layer that gives your end users, the ability to not have to translate between kind of the.

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Ethan Post: The technical diagrams of the data that's being pulled in from netsuite or any other system and what they want to do with it right so i'll look at something like this NS common schema.

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Ethan Post: and be able to tell you okay well here's some core filter criteria we pulled in here things like account type account number transaction type.

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Ethan Post: all the way down to transaction line details around calculations for things like open ar amount potentially you know item quantities for sales orders purchase orders.

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Ethan Post: The whole the whole night right, so the idea here is the blueprint comes pre packaged with kind of this translation layer that gives your business users, the ability to kind of.

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Ethan Post: As Brian mentioned just added go right stand up in court, a stand up that blueprint connect to your instance and it basically works in a matter of typically a couple hours.

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Ethan Post: On the back end I love talking to technical teams, because we kind of speak the same language so.

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Ethan Post: I tend to dive into the weeds in terms of the data model, the complexity of the scheme wasn't so on and so forth.

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Ethan Post: So when I dive into something like i'll kind of pick on this this netsuite entity schema for us today right, this is want to spend a lot of time.

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Ethan Post: Because, as we move forward right snapshot and typically applies to things like slowly changing dimensions.

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Ethan Post: But the idea here is that in court has already done all the plumbing around you know, taking netsuite entity tables things like customers sales REPS other other kind of identity or entity dimensional attributes.

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Ethan Post: And joining them onto things like transactional data to get things like inventory item or location inventory and things of that nature right so.

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Ethan Post: All that to say that you know the the businesses expectation of it and the analytics team has kind of superheroes are magicians.

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Ethan Post: That low bar is pretty easily met by that in quarterly print right and the idea is.

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Ethan Post: hey we come with all this pre packaged content, you know business schema schema that allow it to be up and running.

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Ethan Post: On the standard delivered fields in netsuite has so let's add one more layer of complexity under that saying okay.

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Ethan Post: Your end users have said Look, we need a better solution for reporting on top of netsuite you can deliver them this set of blueprints that gives them this kind of standard out of the box content.

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Ethan Post: But what happens when somebody turns around and says okay well you know it's great that the quarter blueprint for netsuite.

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Ethan Post: You know i'll pick on one particular report here right if I look at something like my order summary dashboard so this relates all sales orders.

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Ethan Post: I can get some pretty rich information around you know, the number of transactions customers items in quantities, as well as revenue generated from various customers and sales orders.

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Ethan Post: and say I had this table down here right, which gives me order by customer.

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Ethan Post: If I have say an end user who says look This is great, I can see orders by customer.

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Ethan Post: What I don't have in this scenario is the ability to drill further into customers, because some organizations might have you know particular to say customer type other customer dimensions that haven't been pulled into our blueprint.

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Ethan Post: So to brian's initial point.

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Ethan Post: kind of that first layer of complexity that i'll bake On top of this use cases Okay, now they want additional fields that are not contained within our blueprint.

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Ethan Post: So, luckily I mean that's what does a great job actually of not only publishing their data model, but making access to these underlying system tables very open.

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Ethan Post: So what we've actually built as part of the blueprint, and this is catering specifically to a technical audience.

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Ethan Post: Is this concept of okay we're going to tell you exactly what fields and tables existing or netsuite environment from these netsuite system tables.

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Ethan Post: We can also do the same thing inside of in quarter to tell you that hey we actually have about say 1000 fields we brought in from our netsuite instance in this blueprint right.

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Ethan Post: In our notes, we didn't since we have some customizations for this kind of internal instance i'm using now.

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Ethan Post: Probably not anywhere near as much as normal organization may but there's about 8000 fields we haven't brought in right.

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Ethan Post: And I can see that same thing at that at the table level, so you can see, the majority of tables here actually have not been brought into our blueprint.

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Ethan Post: But things like you know accounting periods accounts other key tables have been brought it right okay so so say that a customer is requesting customer contact information.

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Ethan Post: You as an IT organization can come up to this dashboard say okay well all I really need to do is find a table name called contacts that I can search for pretty easily.

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Ethan Post: Come to find out hey that's not being done mean quarter blueprint because oftentimes there's a lot of heavy customization here right.

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Ethan Post: You can find the entire list of fields contained in this table as well as some key attributes around you know field type length and so on, so forth.

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Ethan Post: Okay, so that's step number one is identifying all right, well, I have an end user here who needs an additional set of information.

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Ethan Post: But then the question becomes how easy, is it for me to take you know this kind of newfound insight on what we don't have.

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Ethan Post: In bacon into the blueprint so i'm going to do this right in front of our eyes, right here.

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Ethan Post: And what i'm going to do is leverage another set of system tables and netsuite provides around foreign keys and Jones right.

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Ethan Post: So if I take the same table, and I look at that contacts right and i'm going to look at the the primary key for contact right.

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Ethan Post: Come to find out that netsuite basically publishes all the genes that are available for that context table and it actually joins directly to the customer table based on a field called primary contact ID.

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Ethan Post: Okay, so I basically have everything I need now, I understand there's 80 some odd fields inside this context table and if I want to give my my end users, the ability to now create say contact information on any customer related insight.

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Ethan Post: I kind of have a roadmap to build that in right so i'm just going to do that here, in real time, so if I go back into that entity schema.

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Ethan Post: One thing I can do is leverage our schema wizard so you know for technical folks might not be as huge of a deal but think about the concept of.

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Ethan Post: A no code approach to bringing additional data right so i'm not going to write a single line of code here i'm going to go through this wizard to go ahead and pull in our context table.

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Ethan Post: right with all at one field that we identified on that that first dashboard and i'm just going to pull it in you in quarter.

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Ethan Post: Now the other thing I have at my fingertips, is the concept that I already know the joint between these two tables because I leverage that internal some of the reporting that we built for technical teams to determine that there's a field in here called primary contact ID I believe.

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Ethan Post: That just joins out to this field here called contact ID my context.

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Ethan Post: Okay, so in you know, probably five or six clicks of a mouse, I have not gone ahead and add to that context table I joined it out to my existing customer table and the last thing i'm going to need to do here is go ahead and load our context table.

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Ethan Post: With data right.

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Ethan Post: So now, and you know, a couple minutes we've extended upon this kind of delivered in quarter blueprint.

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Ethan Post: And the idea here is, you know i'll kind of stick with this theme of the IT team has kind of the behind the scenes magicians right.

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Ethan Post: Think about that data warehousing process and what you'd have to do to bring that data through the various steps in the chain.

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Ethan Post: Within coordinates it's a couple of easy clicks of a mouse, and because of the fact that all we're really doing is connecting out to a source system like netsuite directly.

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Ethan Post: I can pull that table in exactly as it exists join it out to my customer data.

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Ethan Post: And all of a sudden now, if I can find that contact table right so now, I have this joining you that gives me the ability to extend anything inside my blueprint with now contact information for a given customer.

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Ethan Post: So let's take another you know another example of what that actually looks like in the field.

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Ethan Post: Right, so I come out to the same dashboard and all of a sudden, I can update this orders by customer with new key contact information so i'll just go out to that.

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Ethan Post: That schema that we just identified and pull in addition to my customer table pulling contacts and maybe I want to just go ahead and.

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Ethan Post: Look at that particular table right, so I can pull on any of these fields that I want to write email, fax so on and so forth.

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Ethan Post: What I can do i'm just going to search for name here real quick just to make it easier on myself.

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Ethan Post: And pulling the contact me so we're going to find out to say not every account, not every customer actually has a contact, but for those that do have a primary contact listed.

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Ethan Post: i'm now giving my end users, the ability to extend that kind of pre built dashboard into something that might be more useful for them right.

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Ethan Post: So there's obviously practical applications this, but the idea here, especially the value for our technical team.

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Ethan Post: Is you're not going through you know months of requirements gathering in terms of hey let's let's bake in all of the end users use cases that we have or might need to fulfill.

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Ethan Post: and building that into ones in kind of like a one shot approach, so this is very eXtensible super configurable and we've given you kind of all the tools, you need to identify what's here what's not here and how easy, is it to add so that's kind of the first level of complexity right.

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Ethan Post: The next thing that might happen, say, the next day you come to your office and you're getting a phone call from you know sales territory manager saying hey.

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Ethan Post: This blueprint is great, it gives me access to all the information I need, but my sales team doesn't need access to say you know the worldwide view of revenue right So if I go to this revenue summary dashboard.

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Ethan Post: Basically, anyone out of the box is going to be able to see things like global sales across the whole organization right so then include sales for US, Canada and then even parts of Europe.

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Ethan Post: So your sales territory manager might say look, I want to lock this data down I don't want to an individual sales REP to be able to see anything outside of their own accounts.

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Ethan Post: And according to brian's point is specifically tailored to allow that to think of the concept of pulling the next week data, indirectly, as it exists inside that source system gives us the ability to finally manage how that security is actually portrayed within corner.

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Ethan Post: So i'm just going to take you know one quick step to go back to those some of those system tables.

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Ethan Post: And one other thing we've done is actually just pulled in the user roles information tables so obviously netsuite has a ton of these right.

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Ethan Post: The idea is inside netsuite proper you map a user to a role and each role has specific permissions whether that's by subsidiary department company.

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Ethan Post: In the case of a sales REP you actually can even lock that down by particular customer account.

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Ethan Post: down to the level Okay, I want to make sure any sales REP can only see his or her activity right so i'm going to stick with that that top REP So if you.

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Ethan Post: had seen inside of that that dashboard I just brought up our top REP here corporate is Mary running.

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Ethan Post: So i'm gonna use her as a quick example and say okay well she has one role here 1005, which is an inside sales representative.

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Ethan Post: So I can come down here and see all the entities that that Mary might have access to if I wanted to I can even build that content for things like subsidiaries departments and so on.

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Ethan Post: But for this particular use case right i've had a sales manager come on here and say, I only want Mary ready to have access to the accounts are the customers that she supports so it's pretty simple right.

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Ethan Post: i've taken this concept of on a customer table you have basically the sales REP who supports them so i'll go back out to my my entity schema and i'm just going to pull in here a couple quick fields, from our customer team so.

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Ethan Post: So i'm going to pull in my company name i'll also pull in my.

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Ethan Post: Sales REP ID for my sales are cable and what you're basically going to see it as well, so I don't feel.

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Ethan Post: Appalling sales REP ID from the customer table and for any sales REP basically there are assigned to a specific set of customers right so Mary running happens actually sales REP 1008.

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Ethan Post: So what i'll do here really quickly is just pull in Mary readings data only and here's basically you know the.

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Ethan Post: The list of customers that Mary should be able to see right so there's 204 customers that she is listed as the kind of the direct sales REP on.

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Ethan Post: And all I really done is that okay well taking this information, I have an employee table which lists Mary writing in her employee ID.

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Ethan Post: I have a sales REP table which lists companies, as well as the REP responsible, so all i've done at the transaction line level, and this is going to be important to understand is i've applied to filter that basically goes through, and.

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Ethan Post: and identifies for each transaction of the transaction line level i'm going to go ahead and say okay well on the front end and quarter, basically, what I want to do is.

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Ethan Post: filters sales REP ID by a filter that i've defined here is a variable so Mary reading logs into a quarter.

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Ethan Post: She sees that that sales REP filter is 1008 meaning she can only see customers that have sales REP 1008 as kind of their their primary sales REP right, so all that to say if I go ahead and kind of impersonate me reading here on the front end.

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Ethan Post: i'll go back out to that encoded dashboard here pretty quickly we'll see not the population of data that everyone else can see i'm gonna go back to our revenue summary dashboard.

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Ethan Post: And we're going to see kind of a more i'd say you know sporadic view of the data that's represented here right So if I look at sales.

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Ethan Post: Right now, no sales in Canada, because mayor REP doesn't support any accounts and Canada, and you basically have kind of a you know, a pretty.

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Ethan Post: Well, distributed customer list throughout the us a few more in California, then across the rest of the United States, but you know basically i'm looking at the city level.

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Ethan Post: accounts that that Mary reading supports and the cool thing is, you know.

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Ethan Post: As long as your end users are aware of this, you know that that functionality, is going to carry through from netsuite So the idea is anything they can see in netsuite they can also see any quarter.

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Ethan Post: But they're almost going to be used to kind of seeing this slice of the world anyway right so Mary reading is only looking at about $5 million of revenue coming in.

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Ethan Post: Throughout time for the account so she supports and that's kind of the idea right here's all the customers, or maybe reading supports are actually revenue generating which is 118.

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Ethan Post: But if I go out to kind of again the population view what you're going to see for anyone that's not listed as a sales REP or doesn't have that same level security applied.

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Ethan Post: All of a sudden you're getting kind of that population level right.

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Ethan Post: So that's kind of the idea of not baking on this complex concept of okay now we've understood how we can kind of extending configure the blueprint.

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Ethan Post: For an IT team, you also need to understand the view work data governance and data security, which included just inherits directly from that source system.

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Ethan Post: Right, so making it super easy to not have to maintain two separate sets of transaction level security.

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Ethan Post: And the last kind of piece of complexity that out i'll bake on top of years basically.

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Ethan Post: The magician's trick of basically for me data out of thin air right so netsuite proper so i'll kind of stick with the theme of a sales order that Brian mentioned.

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Ethan Post: So if I have a sales order and i'm an organization, who does things like you know, quoting or has sales orders that are.

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Ethan Post: entered well in advance, there can be a lot of variability from the time of sales orders entered to the time that we actually receive you know revenue from that sales order.

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Ethan Post: So the idea here is, I hear from a lot of organization to say hey it'd be great to be able to track changes over time, this also obviously applies to things like inventory levels or.

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Ethan Post: master data so tracking slowly changing dimensions on things like customers employees and the like.

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Ethan Post: But i'm going to do is walk us through a really quick example of how easy it is to do that inside corner.

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Ethan Post: So I kind of showed you all the based you know transaction level data that we can pull into in quarter.

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Ethan Post: But I have another schema here called transaction snapshot and i've done a couple things to kind of illustrate the various ways in which this can be done.

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Ethan Post: But the idea here is, we have a transaction table and a transaction lines table and i'll just stick with the example of transaction lines here.

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Ethan Post: The idea is in quarter can load data incrementally from netsuite meaning basically every time you load the schema it's going to reach out to netsuite and look at that transaction lines table inside netsuite.

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Ethan Post: And look at the last last modified date to determine what changes have been made since the last time that data was loaded in quarter right.

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Ethan Post: So the implications of that are I can set a key here it's basically that last modified date, plus the actual record level key.

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Ethan Post: For that record inside of netsuite so What this means is rather than actually updating the data as you would see in netsuite as a source system.

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Ethan Post: We can actually insert records based on changes so now, if you have a sales order and update that sales order you'll not see two separate records for the same transaction line from that same transaction.

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Ethan Post: Now, again, the implications of this are pretty awesome because what you allow incorporated you is kind of assume that responsibility that a traditional data warehouse would have to take.

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Ethan Post: But cut out the you know six to seven months of building and who knows how much spend in order to actually get that up and running and fully tested.

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Ethan Post: The other concept here is this concept of dense snapshot and.

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Ethan Post: So while you may want to you know for something like sales orders which have the potential to change over time.

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Ethan Post: If you think of something like inventory levels right maybe you want a daily snapshot of inventory levels, regardless of it, they changed or not.

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Ethan Post: So this concept of a dense snapshot i'll just cover really, really quickly is also key to understand.

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Ethan Post: In saying now i'm not looking at that last modified date i'm actually keying off assistant, which says every single time I load this table basically take the population, the entire set of transaction lines.

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Ethan Post: And append them to the bottom right, so this is a bowl insert of that every single time that tables run so i'll give you a quick example of how this actually works in the one right so i'll go into netsuite proper and i'll look for.

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Ethan Post: A specific orbs.

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Ethan Post: Specific sales order so I have a sales order here those place to 3am.

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Ethan Post: I think in a second year will see that this is a sales order this pending approval right so it's still in the approval process not yet finalized meaning at any given point I can come in here, and I can actually edit quantities.

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Ethan Post: So there's three items on the sales order and there's kind of a set amount of quantity that was created when the sales order was first put in place, but maybe for whatever reason, you know.

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Ethan Post: The sales REP on this on this deal wants to come out and maybe reading actually didn't sell five units of this particular item she actually went out and sold.

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Ethan Post: Maybe 25 right, so we can update those those quantities and I can save the sales order and again the concept behind the scenes is.

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Ethan Post: Now that I made that change to brian's point you know I can take a look at this this audit trail and say hey here's a change that was made to this transaction, and we can kind of get the total here.

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Ethan Post: wouldn't quarter provides you the ability to do is come through and actually load incrementally to get that snapshot right.

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Ethan Post: So I kind of talked to what's happening in real time, as I load this data incrementally so obviously a records change in netsuite that specific transaction that we just looked into.

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Ethan Post: So at the transaction line in the transactions level.

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Ethan Post: we're basically going to append a record for that change transaction and that dense snapshot you're going to see here in a second is going to go from I think right around.

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Ethan Post: 150,000 records representing the sum total of transaction lines inside of our netsuite instance to I think something around.

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Ethan Post: 300,000 if i'm not mistaken right so 234,000 records right which is 156 times too, so the idea here.

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Brian Keare: Is a lot of different ways to kind of.

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Ethan Post: manage this concept of snapshots right, so how this actually works on the front end, I think, is what really kind of ties, all this together, because it's the idea of for an end user.

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Ethan Post: Now they basically get access to to any one transaction that they want to look into, but I can say okay here's my sales order six or two.

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Ethan Post: notice that it's actually been changed, three times inside initially loaded this data right So if I scroll down here I not only get access to that first time that transactions enter in which we're looking at 250 units and about $13,000 worth of.

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Ethan Post: You know amount on that sales order to now 175 units representing the 25 and 50 that I just put in which actually brings that up to $25,995 right.

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Ethan Post: So, think about the idea being able to turn this over time and doing analysis around okay well if people are updating sales orders your inventory levels of changing.

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Ethan Post: Why is that, is there any correlation to changing quantities and sales orders and the ability to close business right.

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Ethan Post: So, at the end of the day when a quarter really provides you is a visualization suite that can take this concept of changes over time and give you this trending analysis right.

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Ethan Post: So i'm looking particularly at this this item here the CEOs years or two, and I can say okay started at about 250 units went to honored and stated 100 but at the same time i've increased the other.

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Ethan Post: The other item quantities on the sales order right so again i'm talking to a technical crowd here and that's a fairly technical talk track.

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Ethan Post: But the idea here is taking that basic blueprint that we've kind of talked to three or four times now on these sessions.

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Ethan Post: which provides the end users, a lot of flexibility and a lot of functionality, but as an IT organization that concerns always okay that's great but.

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Ethan Post: How easy, is it to change how scalable is this, and I think we've seen it's highly configurable based upon your netsuite instance in the specifics of the way you do the business.

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Ethan Post: Highly configurable in terms of who gets access to one who can see what data based upon netsuite native security rules.

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Ethan Post: And then finally configure configurable and extending that netsuite functionality to say things like inventory sales orders or anything you want to track over time.

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Ethan Post: You now get access to actually view in real time, as opposed to having to build some complex solution to handle these challenges.

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Ethan Post: So i'll pause there I know that's that's a lot of talking for me and certainly a lot of content to cover in a short amount of time, Brian or phil i'm interested to hear you know your guys thoughts in terms of translating this to the value for technical teams.

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Phil Reinhart: sure.

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Phil Reinhart: And I mean, I think.

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Phil Reinhart: Also, you know that you covered you've covered a lot of different.

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Phil Reinhart: Areas that in quotes can be valuable and, at the end of the day, I always go back to you okay how am I going to get how am I going to get top line impact.

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Phil Reinhart: Out of this solution like in, especially in a time like this, where you're trying to figure out Okay, how can we pick up dollars in this type of economy.

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Phil Reinhart: And, and I think of you know as you're going through the dashboard thing and.

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Phil Reinhart: You know I think of Okay, who were who were the or people in my organization or my customers that are going to be making those in the moment decisions.

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Phil Reinhart: And, and how What are those decisions what area of the business are those decisions being made, and how are those decisions going to get an impact, you know our top or bottom line and.

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Phil Reinhart: And so anyways, I just wanted to maybe just a thought, you know as as you go through all that, like.

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Phil Reinhart: You know where do you, is it the executives that are getting the most benefit out of the dashboards is it is it the individual contributor, is it is it, maybe even just directly to the customer, where do you see that you know when the rubber hits the road.

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Phil Reinhart: And we've got this implemented like who who's really being impacted.

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Brian Keare: From, from my perspective, in my experience at North tech it's it's really you know I ran the it team our it team went overnights.

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Brian Keare: from being the folks that you know, we had offices and people would be coming to our offices saying.

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Brian Keare: gosh you guys, I asked her this two weeks ago you haven't delivered my ability to report on you know this new dimension that we just.

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Brian Keare: lit up or this new system that we just incorporated into our you know that I just gave you into my dashboards and so what's going on.

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Brian Keare: We transform that kind of we were the you know the whipping team, or you know, whatever whatever the metaphor is that people got mad at to.

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Brian Keare: In many respects we became the heroes, because we were able to achieve a measure of instant gratification and being able to answer much more quickly.

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Brian Keare: These challenges and these questions for that came from executives department heads or analysts in the field, and we also empower them.

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Brian Keare: To do their work on their own, we were able to say hey you can do a lot of this on your own we set it up, and you can go with it, and do it on your own.

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Brian Keare: And that's really a game changer, so I think that you know what it does for the it team is it actually makes you heroes as as opposed to somebody who seems to.

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Brian Keare: be getting yelled at all the time, and you have to juggle competing priorities, but you know one thing i'd love to redirect to ethan is.

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Brian Keare: You know, one of the things that we haven't touched about advanced analytics are the ability to move from.

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Brian Keare: To add on to the operational analytic framework that we've talked about today and we've talked about in general and say.

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Brian Keare: hey you know I know the buzzwords of predictive analytics I know the buzzwords of machine learning and Ai.

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Brian Keare: Is there anything that in court, I could offer that actually gives me the ability to do some of that as easily as we can do some of these operational analytics things that you've done, and you know.

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Brian Keare: i'll leave it to you ethan to talk about your experiences I could talk about one nor tech but.

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Brian Keare: You know I think that's another thing that I think we can begin to touch on and then continue the conversation with anyone who's interested.

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Brian Keare: In exploring that further with us because it's pretty pretty straightforward and easy to accomplish and in quarter, like some of these other things that we've done ethan.

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Brian Keare: What are your thoughts so.

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Ethan Post: really interesting question, I mean, I think.

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Ethan Post: You know the the ml data science spaces is getting so vast that there's a library of tools that are dedicated specifically for that right.

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Ethan Post: And every organization, I talked to you, whether they have a team of dedicated data scientist, or whether they're just kind of you know kicking the tires on it will say hey.

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Ethan Post: I have kind of this white whale scenario where, if I can figure out this one piece of information, if I can predict who's going to turn.

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Ethan Post: it's going to completely change my business.

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Ethan Post: The challenge they always have is even if I have the best data scientists know like where do I even get that data from how do I have the capability putting all this data together in one place to answer that question.

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Ethan Post: And I think that's what it really brings to the table in terms of data, science and machine learning is.

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Ethan Post: This is holistic view of all your business and all your data source so we've talked about netsuite but talk to any of our customers and they're looking at multiple 5678 sources in a single.

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Ethan Post: instance, and what that provides you the ability to do is any research you go out to and take a look at.

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Ethan Post: 75 to 80% of the time of data scientists spent is wrangling scrubbing data in quarter cuts that out, full stop and says look your data scientists do data science so.

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Ethan Post: I think there's a lot of value to be done there, and I mean something i'm particularly interested in is this concept of baking in some of these data science concepts into our blueprint so thinking through.

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Ethan Post: Every every Organization has eyes on things like predicting customer churn specifically being able to look at like accounts receivable predict who's going to pay and how long it's going to take.

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Ethan Post: and frankly there's some common threads are common themes throughout every organization, I talked to that has the you know the capabilities to do this, and I think.

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Ethan Post: that's something I think we're even looking at building out more you know operationalize as part of that blueprint so there's my soapbox I appreciate the question I think it's something i'm obviously pretty passionate about but yeah right i'll see it up to you.

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Brian Keare: Great I think that that you know, I think that that hopefully give folks a taste have.

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Brian Keare: a taste of how in court, it can change the game for teams that are interested in it analytics advanced analytics and being able to deliver some advanced tools directly to their end users and to empower them.

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Brian Keare: So I think i'll leave it to you phil to wrap up to talk about the October value sprints and you know, to reiterate that.

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Brian Keare: And I think we've touched we've touched on many of these subjects, I think the good news is that if anybody wants to actually explore these in more detail.

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Brian Keare: We don't have to set up a complicated multi month proof of concept.

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Brian Keare: You can sign up for your own trial, you can get your own blueprint in your own trial instance, you can connect your own data.

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Brian Keare: And within a matter of minutes or hours you can actually start seeing some of your own data inside of encarta in these ways and see for yourself how easy it is to do some of these things so over to you yeah.

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Brian Keare: and

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Brian Keare: I mean.

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Phil Reinhart: Just going off of that right, we have this value sprint and and you know we're not the old school.

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Phil Reinhart: Technology company, where you know 21st century here, we want you to try the technology before we ask you to move forward with us and we want you to not just try it and.

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Phil Reinhart: Do a proof of concept, but we want you to solve it and get to an outcome in a matter of weeks, and you know we're here to to throw our time and our talent or technology at you all.

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Phil Reinhart: To to accomplish that and we want you know the gnarly Harry you know difficult challenge that you think is going to take two years, and you know, like, for example, at one of the largest.

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Phil Reinhart: You know, coffee retailers we they had a basically a two year project that we turned into 11 weeks, and in part of that we help them increase some of their food sales and reduce food waste and so there's there is an opportunity here where we're we're taking very long lengthy.

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Phil Reinhart: Data initiatives and shortening into to matter weeks and we're here to make that happen and value sprint I mean that's really that's the core story here.

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Phil Reinhart: And so yeah.

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Phil Reinhart: Next slide please you think.

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Phil Reinhart: The cords a trial is available@cloud.com so we're not you know hiding behind the curtain here, you can go out and try and quarter right now.

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Phil Reinhart: And there's no, you know download the S go on your desktop where you have to get an approval from it, you can access in court to directly through your browser and start trying it today.

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Phil Reinhart: So it's it's right there, and you can you can see the speed that we've been talking about and upload data and give it a go, and this is something that you can do without even contacting us.

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Phil Reinhart: You know you don't need to call you know me a sales guy or even a you know, a sales engineer, you can you can get going yourself give it a try.

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Phil Reinhart: All the sessions from the four from the series are going to be available all the recordings, so you can access those right there in the link that we've posted and then.

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Phil Reinhart: And that's presented, I think it's less I know that's it Oh, and then just a reminder yeah just a reminder invite your peers to watch the recordings we've got the.

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Phil Reinhart: This series out there, we have the value sprint available to to you and your peers your colleagues and connect with us, we want to talk so anyways Thank you so much, everybody for attending this series, and we look forward to.

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Phil Reinhart: talking with you and solving some of these use cases.

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Phil Reinhart: Any any questions, I think we we got four minutes yeah questions that might be out there.

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Phil Reinhart: I did have I wanted to kind of follow up on the.

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Phil Reinhart: The conversation you guys are having around the time value of data and just wanted to make a mention that.

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Phil Reinhart: I i've seen a couple studies come out one from Harvard about how the time value of data is is very much.

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Phil Reinhart: A critical piece of your Ai and machine learning models and if you're not getting the data.

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Phil Reinhart: To the models fast enough, and if you're not getting enough of the data to the models fast not fast enough just historically and the current moment data your models that you've invested maybe you know, three or four data.

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Phil Reinhart: Scientists to build over the last six months aren't going to produce the outcomes that you sought to see you know.

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Phil Reinhart: To.

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Brian Keare: Go after and so.

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Phil Reinhart: I think that's a key very important factor is like it costs so much take so much time to get there and then.

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Phil Reinhart: All of a sudden, you know you're you're not able to get the data to those models fast enough or you're not in a you're not able to get down to that that detailed level for those models to matter.

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Phil Reinhart: So I just wanted to point that out it's it's I think you know coming from the all tricks world and some other diet data science worlds, you know before all in court to that really speaks to me.

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Ethan Post: So yeah.

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Brian Keare: Good point I just ECHO ethan's comment, which is that you've already got all that data, you know real time operational data inside of in quarter and instead of having to.

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Brian Keare: Have a project that offloads that for use elsewhere, the philosophy of in quarter is make that same data available to data scientists to anybody who needs it.

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Brian Keare: And it's easy to understand, easy to use, you don't need to flatten it you don't need to shape it grab it as it is and do your analytics on top of it do your ml Ai.

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Brian Keare: predictive analytics on top of it, in addition to your operational analytics and so it's always there you don't need to.

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Brian Keare: You don't need to have success of projects, and so, if you want to go back and test your model you take the data or.

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Brian Keare: You know, a portion of subset of the data to your do your modeling on and then you go and do your regression testing against the rest of the data.

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Brian Keare: Inside of encoded validate your model from an operational perspective, so the cycle times of being able to create models and then go back and test them against actual data those cycle times are super quick so for folks who want to get into the advanced analytics portion of things.

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Phil Reinhart: You see a lot of data science tools out there, I mean what does that look like mean if i'm doing something in SAS or did briggs or all tricks, or you know data IQ you know name your data science tool How does that work with all this.

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Brian Keare: yeah.

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Brian Keare: I think we're at time that might be, it might be a big question for another day we're going to get in that one, I think.

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Brian Keare: phil and say you know, for those of you who want to dive down into that I think we're scratching the surface, but those are really great questions, and you know we'd love to talk to anybody about about them, so thank you.

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Brian Keare: You know, thank the person in the audience for that question, but I think we'll you know not not.

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Brian Keare: We would love to talk to you further about it just contact any one of us, and we can show you a little bit show show you around the quarter platform and show you what we can do in that respect awesome.

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Phil Reinhart: Alright guys well have a great day.

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Phil Reinhart: And thank you for attending.

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Thanks cheers.

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Phil Reinhart: Hello everybody Hello Hello Hello welcome welcome welcome.

 

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Phil Reinhart: we're going to let everyone trip plan a little bit here, and then we will go ahead and get started in a minute or two while everybody gets a situated with their video and their audio and everything.

 

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Phil Reinhart: As always, I do have a couple jokes.

 

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Phil Reinhart: they're not great.

 

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Phil Reinhart: I kind of laugh at myself it's actually kind of cringe worthy matter of fact, but we're gonna say and tell them anyways because we all want to hear them.

 

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Phil Reinhart: um so here's the first one it's quite short and it's really bad who's the father of data.

 

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Brian Keare: No, no phil who.

 

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data.

 

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Ethan Post: I gotta be honest that that actually might be the best one which is probably what.

 

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Ethan Post: A compliment that you think.

 

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Phil Reinhart: No, I didn't even really try come on all right here's no there's no.

 

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Phil Reinhart: I collected, a lot of data, trying to disprove disprove confirmation bias, the results were exactly what I expected.

 

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Phil Reinhart: Alright, well, let that one just see been maybe you're gonna laugh like in an.

 

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Brian Keare: hour that work.

 

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Brian Keare: That work.

 

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Brian Keare: I got it awesome.

 

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Phil Reinhart: Thank you well, those are the two I have for today.

 

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Brian Keare: Confirmation bias i'll.

 

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Phil Reinhart: Try to work in a couple more as we go.

 

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Phil Reinhart: Through but anyways hi everybody, welcome to our webinar today in quarter, for it analytics my name is spelt reinhardt I am the i'm a sales guy here in quarter and i'll be your moderator for today.

 

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Phil Reinhart: Just some quick high level call to actions that I just are actually before we get into that housekeeping before we begin.

 

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Phil Reinhart: If you have any questions during the presentation, please type them into the Q amp a box and anytime you can reach out to me directly in the in the chat box as well if you don't want it to be public.

 

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Phil Reinhart: i'll reach out to all of you can make comments funny jokes whatever you can make fun of me, whatever you want just you know, we want to hear from you and.

 

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Phil Reinhart: Also, you know if you want to reach out to us afterwards you've got our names, you can find us on linkedin we are you know definitely open to communicating and we'd love to meet and and talk about you know what's on your mind and and where you see data going today.

 

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Phil Reinhart: So some call to actions in the agenda, we we really want to point out that here, in October and really all Q4 we have this program called a value sprint.

 

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Phil Reinhart: And what this value sprint really allows you to do it, it gives you our time our talent and our technology to be able to solve up to two use cases and not only we.

 

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Phil Reinhart: Just you know, not only are we showing you how important works, but we're actually proving out and getting outcomes, so we want to, we want to find a problem in your business where you see their.

 

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Phil Reinhart: pop in May may be opportunity for top line dollar impact or a process improvement, maybe some fit savings and cost containment.

 

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Phil Reinhart: Wherever you see that opportunity we want to team up with you give you, you know teach you how to fish but also go out and solve those problems and realize those you know with your business partners.

 

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Phil Reinhart: Over that value sprint so that's definitely you know, the call to action after this webinar we also have all of the sessions that we've done throughout this entire series recorded, so those will all be available to you.

 

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Phil Reinhart: And will be will send it out we'll be sending it out via email, so that you have easy access but definitely reach out to us about the value sprint.

 

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Phil Reinhart: So now i'd like to introduce our speakers today, so you know as always we've got Brian here and ethan Brian he's our CIO here in quarter, he was the CIO over at Norton security and actually launched.

 

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Phil Reinhart: In court to their he almost made and what we call it in an ocean moment that turned into an Aha moment, where he was about to spend millions of dollars.

 

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Phil Reinhart: On their data strategy in a different direction and chose to go within core data and it saved them.

 

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Phil Reinhart: During the tariffs last year, the big tear of changes that affected the nor tech business and then he ultimately decided to join in courts that because.

 

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Phil Reinhart: of how much it revolutionized his perspective on data so that's Brian and then we also even he's the head of courses pre sales Center enablement here.

 

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Phil Reinhart: he's got three years of experience here in courts and he's going to career of implementing different systems across beyond analytics because he's got a very broad perspective.

 

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Phil Reinhart: In your world that he can really bring to to the call today so that's who's talking, today, and so without further ado i'll hand it over to Brian to kick us off and ethan's gonna gonna run slides for us, thank you.

 

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Brian Keare: Great thanks so much phil really appreciate it i'm coming in audio only today, because I am the unfortunate.

 

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Brian Keare: Unfortunately, am reliant on spectrum business for Internet here in Los Angeles, and it looks like spectrum is having huge problem in Los Angeles and across the country.

 

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Brian Keare: So So hopefully this will come through if not i've got my team mates to jump in and help out, so what we're going to talk about today is in quarter, for it and analytics.

 

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Brian Keare: But let's take a quick step back and give you context, some of you who have participated in our previous webinars over the past few weeks, and thank you for joining.

 

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Brian Keare: Have gotten a little bit of this context, but I think it's important to re establish it just before we jump into some of the finer points that that it cares about and with respect to advanced analytics.

 

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Brian Keare: So as phil said before I came to encarta I was, I was CIO Iran business systems and data analytics that North tech nore tech is a global manufacturer of smart products for small businesses and for homes and we had pretty complicated, we had a pretty complicated ecosystem that covered.

 

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Brian Keare: You know, multiple continents countries currencies thousands of employees dozens of locations.

 

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Brian Keare: How did we run nor tech well at the Center of how we ran it was indeed netsuite we found netsuite to be.

 

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Brian Keare: An extremely capable system that allowed us to manage our global business in multiple currencies and I think we were pretty great at.

 

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Brian Keare: At using netsuite to power, our global business, so we would build dashboards that would give us a bird's eye view of what was going on here is an example of that.

 

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Brian Keare: But I think is, those of you who are familiar with netsuite know once you get into.

 

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Brian Keare: netsuite and trying to manage business you quickly find yourself navigating from page to page and so next slide talks about an example, if I have a KPI and I want to drill down from a KPI into something my view my browser switches and all of a sudden, I go to a individual report.

 

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Brian Keare: So many of us if we're very adept at doing this, we will do this constantly and we might end up having 75 different tabs open that reflect dashboards plus reports are saved searches.

 

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Brian Keare: As we get more sophisticated in how we leverage the tools that are available to us in netsuite we might create a safe search that we then put on on our main dashboard.

 

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Brian Keare: So here's An example of this, where i've got to save search and different folks throughout you know the hundreds, thousands of people in our company would have different dashboards that they wouldn't manage their day with.

 

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Brian Keare: And they would have you know, in this case open purchase orders in other cases, it would be managing supply chain, from the it perspective, it would be.

 

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Brian Keare: How is the system going how well are we processing transactions and so that would be an example of how we would do it, but again once you get into a saved searches, we all know.

 

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Brian Keare: What can you do from there well you click on something, and you can view one transaction at a time.

 

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Brian Keare: So life inside of netsuite is a lot of individual browser windows one transaction at a time and managing one save search at a time, which represents rows and columns of data inside of netsuite.

 

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Brian Keare: A lot of times, we find that when we're doing this that that isn't good enough, and so what do we do we take the results of saved searches and we throw them into excel and XL.

 

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Brian Keare: We believe ends up being empowering for us because I can throw multiple saved searches in there, I could start to add.

 

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Brian Keare: formulas and do a little bit of analytics inside of excel in ways that are eaten may be easier or more familiar for us to do, then inside of netsuite and we have excel in addition to things inside of netsuite that we manage our business with at nor tech.

 

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Brian Keare: Our you know biggest excel spreadsheets would be pretty darn big hundred 64 megabytes.

 

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Brian Keare: encompassing dozens and dozens of worksheets and we would download save searches and manage that whole process.

 

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Brian Keare: So sometimes that gets unwieldy and you can see how, when we'll, be it is from the next slide that describes our business system ecosystem.

 

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Brian Keare: At nor tech, and you can see, although we manage our business in netsuite we would have to bring in data from acquisitions that were on companies run.

 

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Brian Keare: In er piece that might not have been netsuite and so, while we were waiting to integrate them into netsuite we would need to report on them, we had supply chain, we talked about that last time.

 

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Brian Keare: We had distribution wns three PL systems customer facing systems all sorts of systems so as we think about how we can report on data outside of netsuite we brought a lot of that data into netsuite.

 

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Brian Keare: Using tools like Dell boomy but eventually you say hey i've got a bunch of data let's try putting it in a data warehouse to consolidate how we.

 

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Brian Keare: Report on it, so you, you know what's the normal process for doing, creating a data warehouse you create your retail tools you throw it into a data warehouse.

 

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Brian Keare: You get it ready for reporting and in either excel or power bi or tablo in order to do that, you can't just stop at the data warehouse you actually need to model it.

 

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Brian Keare: Create views and cubes that power effectively your visualizations that ends up not being good enough and so i've talked about my story, where we had our Aha moment and still talked about where instead of this process, which was pretty brutal and which would break.

 

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Brian Keare: We found in quarter incorporated really did turn out to be a connected go alternative the team at nortel figured that out over a weekend to prove the value.

 

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Brian Keare: Of in quarter what's the value, I think the next slide sums up what the core value of in quarter is in three easy steps number one you connect your various data sources, including netsuite to in quarter.

 

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Brian Keare: You don't have to reshape it you don't have to do atl you bring it in exactly as it is and ethan will show us some of that today.

 

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Brian Keare: And once it's inside in court, a part of our secret sauce is understanding how that data fits together we just pointed at each other, we don't need to write complex sequel we don't need to reshape it we don't need to flatten it via.

 

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Brian Keare: We don't need to flatten it we don't need to prepare it for cubes and we can start performing modern bi using the built in visualization tools that in court, a house.

 

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Brian Keare: So, from a business perspective, the three ha's really are that, in addition to getting summary aggregation.

 

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Brian Keare: You are able to drill down to row level transactional detail and you're able to flip back and forth, why is this important well it's important because.

 

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Brian Keare: you're not fighting over how somebody's got to those summary level metrics summary level calculations, because you can see, really quickly and validate how those are built up with individual transactions.

 

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Brian Keare: The second thing is that it's a single source of truth, you know that in court, a matches the source system, because there is no reshaping of the data, the data that's in court is exact replica of what's in the source system and so it's really easy to validate CFO is love this.

 

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Brian Keare: And CFO love this because you have a single source of truth third thing is that you got a possibility for true self service, because you know, and this is beginning to get to the point of where it really cares.

 

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Brian Keare: They can empower an analyst who could inside of netsuite create a safe search, they can empower them to do modern complex sophisticated bi dashboard.

 

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Brian Keare: on their own, and you can give your supply chain department, the list of 100 fields that they might be interested in to throw on a dashboard and to start doing modern.

 

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Brian Keare: analytics you can give finance a different set of fields that they might care about, and you can really empower your team.

 

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Brian Keare: To really achieve self service, and that is a huge difference compared to what is the alternative, which is that they're knocking on your door asking you for data asking you to create a power bi report asking you for something that is on your backlog.

 

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Brian Keare: And we all know what that backlog looks like it's really hard to keep up and if you can change the game and empower your teammates.

 

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Brian Keare: To do it on their own to fish for themselves, it really changes the whole nature of the game so that's the Aha for business, I think there's probably a triple Aha for it, and this is really starting to get into the meat of what we're going to go into today number one.

 

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Brian Keare: We we provide a lot of intelligence out of the box we're going to show the blueprints and with respect to netsuite which brings in.

 

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Brian Keare: Standard tables and standard fields, but if, but we all customize the heck out of our source systems netsuite is no different in fact netsuite.

 

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Brian Keare: is more flexible than most in its ability to add custom fields and custom tables those become really important as dimensions to be able to report on.

 

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Brian Keare: In traditional data analytic systems getting new fields and new tables into your data warehouse and reportable is often a very cumbersome process in that suite.

 

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Brian Keare: It can be as easy as a couple of minutes to light up that and ethan's going to show an example of that today so extremely eXtensible and again we are just replicating exactly what is in the source system you add and go.

 

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Brian Keare: The second thing is that we're going to talk about today is that you can mimic your security of your source system in a really easy way, this is no.

 

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Brian Keare: This is no straightforward task, as many of you know, and once you get something into a data warehouse, for example, or index out think about excel.

 

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Brian Keare: And the dumping of data into excel and how all the sudden it becomes really easy to violate what you had set up inside of your source system which might be.

 

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Brian Keare: That only certain people can see certain types of transactions certain transactions only in certain subsidiaries certain departments certain locations.

 

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Brian Keare: Managing that once you allow data csv format xml format data warehouse format to go outside of the source system can be a huge headache and, in fact, many of us throw up our hands and say that's actually an impossible task.

 

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Brian Keare: to accomplish well within quarter it's actually very straightforward to replicate security that you have in your source system and and netsuite is no.

 

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Brian Keare: Different from how we would treat other systems, makes a huge difference and so ethan will show you a little bit about how we can fashion that you know way that ensures that you can deliver.

 

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Brian Keare: Flexibility and data analytics to your team, while maintaining data security it's a huge deal and in court, it is as good as any system i've ever seen.

 

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Brian Keare: at being able to do that in a really straightforward, easy to understand, easy to implement way.

 

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Brian Keare: The third thing that we're going to talk about is that once you have your data replicated inside of incorporated opens up a world of possibilities of advanced analytics that.

 

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Brian Keare: are otherwise unavailable or that would require some really expensive solutions to achieve, and you know I think there's two examples of this, that all that came into play for.

 

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Brian Keare: myself at nor tech all the time number one is creating snapshots of data understanding how.

 

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Brian Keare: transactions, you know I think two areas would that we would focus on would be understanding transactions and how they changed over time, so it could be.

 

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Brian Keare: Open sales orders or estimates that we're waiting for approval and we all know that you know as we're negotiating with customers or customers are putting in change orders those can change over time, or as you're waiting for a.

 

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Brian Keare: An order to be approved the inventory levels that would support, whether or not you could fulfill that sales order might change over time so understanding.

 

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Brian Keare: How those the picture of those sales orders changes over time is something that's pretty hard to.

 

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Brian Keare: pretty hard to do really easy to do inside of encarta same thing with inventory snapshots what was my inventory level of widget X.

 

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Brian Keare: Three weeks ago, two weeks ago, yesterday, a year ago, we can snapshot that really easily in in court and give you.

 

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Brian Keare: You know, let you time travel and take a look at what that was over time it's really a game changer analytics was.

 

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Brian Keare: The second thing is everyone's really talking about predictive analytics ml and Ai and there's a ton of opportunities around that so.

 

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Brian Keare: If we go through the next slides i'll just kind of set up ethan's ethan's DEMO by giving you a quick picture of.

 

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Brian Keare: What it looks like what some of these things look like inside of netsuite, for example, and then how we deal with them inside of how we deal with them inside of.

 

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Brian Keare: In quarter so netsuite you know how do you customize here's an example of you want to add some some.

 

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Brian Keare: custom fields that go on top of your item master this is very familiar to any of you who have customized your netsuite environment.

 

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Brian Keare: What do we do inside of in quarter, well, we give you a very easy to view dashboard across all dimensions, this is the items dashboard it tells you every single field that is in your environment on the item table, whether or not it's a standard netsuite field or custom field.

 

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Brian Keare: And whether it's currently President in quarter or not, and whether it's actually linked to a different kinds of table, so we give all of that intelligence.

 

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Brian Keare: To you, to make it super simple to then add a field and additional field inside of in quarter next slide shows that once you are inside and quarter in you want to take a look at something as simple as the item table, yes, you can see the exact match of what you see inside of netsuite.

 

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Brian Keare: inside of the quarter you add it a couple minutes later you're ready to go and report on it.

 

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Brian Keare: So the next use case talking about permissions and security, the example that we're going to show is related to.

 

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Brian Keare: You know, here is a customer and you know a lot of times we've you know many, many companies will have.

 

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Brian Keare: Customers that are managed by sales REP that's the general way we do things right so some companies care about taking a look at transactions and segregating transactions by sales REP, that is to say.

 

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Brian Keare: If you're a sales REP and part of the sales organization, maybe you only get to see.

 

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Brian Keare: transactions that are related to customers that, for whom you are the sales REP and you don't get to see transactions for other customers so that's a use case that.

 

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Brian Keare: is typical other use cases that are typical relate to limiting the scope of what you see by subsidiary by department by location, all of the different things that you will see in.

 

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Brian Keare: netsuite roles and permissions and so we'll go through an example of that and finally there's an example of a simple sales order inside of.

 

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Brian Keare: Inside of netsuite here's a sales order you know for a certain amount, and you know, maybe you scratch your head or you go around the room and say.

 

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Brian Keare: hey you know didn't these numbers work these numbers different didn't three m, have you know more open sales orders.

 

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Brian Keare: Yesterday, then today what in the world happened inside netsuite what do we do we dive down into system notes, and this is the granularity that you get to see you get to see.

 

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Brian Keare: that yes, Brian wolf changed that sales order and it went down, you know by $1,000 but it doesn't actually give you the granularity that you need to see exactly what happened all you know is that.

 

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Brian Keare: Yes, indeed it did go down you're right your hunch was right, the numbers went down day over day on that sales order pending approval.

 

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Brian Keare: But you don't really have the granularity to understand what the snapshot in time looks like So those are the three things that ethan's going to go over.

 

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Brian Keare: The last thing that I will point out is that you know it's a slide that we talked about previously, which really talks about the value prop of incorporated in terms of time to implement.

 

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Brian Keare: You know the corollary of what ethan is going to show which is once you have it up and running, that it's really easy to change and modify and add and go.

 

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Brian Keare: This shows you how easy it is to implement at North tech we implemented in quarter.

 

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Brian Keare: In the average is one to two months we implemented in one month across the entire enterprise which was a land speed record for any enterprise.

 

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Brian Keare: system that we ever implemented at nor check and you know the comparable implementation of a data warehouse two point O or another complex system would be significantly longer than that so, whether it be.

 

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Brian Keare: Standing up a trial and seeing your own data inside of in quarter or actually implementing it our time to value is second to none and.

 

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Brian Keare: You know I think that's important to take into account ethan will show you some of the power and flexibility here in the DEMO so over to you and ethan thanks so much.

 

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Ethan Post: yeah thanks Brian I appreciate you taking that up and in such a way and kind of walk into the individual use cases.

 

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Ethan Post: Almost take a step back before really diving in the weeds because.

 

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Ethan Post: As phil kind of alluded to, you know i've experienced in post sales and I understand kind of the interplay between the I team analytics organization.

 

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Ethan Post: And the business users who have their own set of requirements right so sometimes i'll kind of like in the the it team to you know what the business users.

 

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Ethan Post: assume sometimes it's like a magician right, so you look at this diagram that Brian speaking to right now and realize that.

 

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Ethan Post: hey we go down this path of a kind of a typical data warehouse we're looking at eight to 24 months.

 

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Ethan Post: But the entire premises of this is that your technical your analytics your bi teams can kind of presume what the end users are going to want to do with the data right.

 

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Ethan Post: So reshaping that data in something like a star schema automatically boxes in your end users in terms of the questions they can answer.

 

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Ethan Post: So when I talk about this DEMO but i'm really going to do is kind of unpacking in a several layers right so layer number one is how quickly, can you get up and running, so if the business things you're a magician.

 

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Ethan Post: what's the magic behind the quarter to actually give you that kind of speed to insight, but also the ability to stand up in court in a couple of weeks.

 

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Ethan Post: and start to give them access to their business data with an unlimited number of questions that they can ask right.

 

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Ethan Post: So let's kind of unpack that for a second, and this is, you know fairly fairly basic in terms of what encoded does and we've kind of talked through this and each of the sessions that we've had so far, but as I log into this encoder instance.

 

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Ethan Post: What you're going to see right off the BAT here after I close out a few of these windows, is this concept of a netsuite blueprint.

 

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Ethan Post: So the beauty of the netsuite blueprint for a quarter, is the fact that it comes pre packaged with a set of dashboards and reporting content right.

 

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Ethan Post: Supporting things like executive reporting finance sales order management operations and so on and so forth.

 

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Ethan Post: It also comes with this middle tier business schema layer that gives your end users, the ability to not have to translate between kind of the.

 

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Ethan Post: The technical diagrams of the data that's being pulled in from netsuite or any other system and what they want to do with it right so i'll look at something like this NS common schema.

 

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Ethan Post: and be able to tell you okay well here's some core filter criteria we pulled in here things like account type account number transaction type.

 

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Ethan Post: all the way down to transaction line details around calculations for things like open ar amount potentially you know item quantities for sales orders purchase orders.

 

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Ethan Post: The whole the whole night right, so the idea here is the blueprint comes pre packaged with kind of this translation layer that gives your business users, the ability to kind of.

 

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Ethan Post: As Brian mentioned just added go right stand up in court, a stand up that blueprint connect to your instance and it basically works in a matter of typically a couple hours.

 

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Ethan Post: On the back end I love talking to technical teams, because we kind of speak the same language so.

 

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Ethan Post: I tend to dive into the weeds in terms of the data model, the complexity of the scheme wasn't so on and so forth.

 

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Ethan Post: So when I dive into something like i'll kind of pick on this this netsuite entity schema for us today right, this is want to spend a lot of time.

 

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Ethan Post: Because, as we move forward right snapshot and typically applies to things like slowly changing dimensions.

 

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Ethan Post: But the idea here is that in court has already done all the plumbing around you know, taking netsuite entity tables things like customers sales REPS other other kind of identity or entity dimensional attributes.

 

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Ethan Post: And joining them onto things like transactional data to get things like inventory item or location inventory and things of that nature right so.

 

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Ethan Post: All that to say that you know the the businesses expectation of it and the analytics team has kind of superheroes are magicians.

 

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Ethan Post: That low bar is pretty easily met by that in quarterly print right and the idea is.

 

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Ethan Post: hey we come with all this pre packaged content, you know business schema schema that allow it to be up and running.

 

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Ethan Post: On the standard delivered fields in netsuite has so let's add one more layer of complexity under that saying okay.

 

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Ethan Post: Your end users have said Look, we need a better solution for reporting on top of netsuite you can deliver them this set of blueprints that gives them this kind of standard out of the box content.

 

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Ethan Post: But what happens when somebody turns around and says okay well you know it's great that the quarter blueprint for netsuite.

 

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Ethan Post: You know i'll pick on one particular report here right if I look at something like my order summary dashboard so this relates all sales orders.

 

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Ethan Post: I can get some pretty rich information around you know, the number of transactions customers items in quantities, as well as revenue generated from various customers and sales orders.

 

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Ethan Post: and say I had this table down here right, which gives me order by customer.

 

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Ethan Post: If I have say an end user who says look This is great, I can see orders by customer.

 

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Ethan Post: What I don't have in this scenario is the ability to drill further into customers, because some organizations might have you know particular to say customer type other customer dimensions that haven't been pulled into our blueprint.

 

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Ethan Post: So to brian's initial point.

 

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Ethan Post: kind of that first layer of complexity that i'll bake On top of this use cases Okay, now they want additional fields that are not contained within our blueprint.

 

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Ethan Post: So, luckily I mean that's what does a great job actually of not only publishing their data model, but making access to these underlying system tables very open.

 

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Ethan Post: So what we've actually built as part of the blueprint, and this is catering specifically to a technical audience.

 

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Ethan Post: Is this concept of okay we're going to tell you exactly what fields and tables existing or netsuite environment from these netsuite system tables.

 

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Ethan Post: We can also do the same thing inside of in quarter to tell you that hey we actually have about say 1000 fields we brought in from our netsuite instance in this blueprint right.

 

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Ethan Post: In our notes, we didn't since we have some customizations for this kind of internal instance i'm using now.

 

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Ethan Post: Probably not anywhere near as much as normal organization may but there's about 8000 fields we haven't brought in right.

 

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Ethan Post: And I can see that same thing at that at the table level, so you can see, the majority of tables here actually have not been brought into our blueprint.

 

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Ethan Post: But things like you know accounting periods accounts other key tables have been brought it right okay so so say that a customer is requesting customer contact information.

 

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Ethan Post: You as an IT organization can come up to this dashboard say okay well all I really need to do is find a table name called contacts that I can search for pretty easily.

 

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Ethan Post: Come to find out hey that's not being done mean quarter blueprint because oftentimes there's a lot of heavy customization here right.

 

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Ethan Post: You can find the entire list of fields contained in this table as well as some key attributes around you know field type length and so on, so forth.

 

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Ethan Post: Okay, so that's step number one is identifying all right, well, I have an end user here who needs an additional set of information.

 

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Ethan Post: But then the question becomes how easy, is it for me to take you know this kind of newfound insight on what we don't have.

 

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Ethan Post: In bacon into the blueprint so i'm going to do this right in front of our eyes, right here.

 

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Ethan Post: And what i'm going to do is leverage another set of system tables and netsuite provides around foreign keys and Jones right.

 

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Ethan Post: So if I take the same table, and I look at that contacts right and i'm going to look at the the primary key for contact right.

 

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Ethan Post: Come to find out that netsuite basically publishes all the genes that are available for that context table and it actually joins directly to the customer table based on a field called primary contact ID.

 

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Ethan Post: Okay, so I basically have everything I need now, I understand there's 80 some odd fields inside this context table and if I want to give my my end users, the ability to now create say contact information on any customer related insight.

 

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Ethan Post: I kind of have a roadmap to build that in right so i'm just going to do that here, in real time, so if I go back into that entity schema.

 

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Ethan Post: One thing I can do is leverage our schema wizard so you know for technical folks might not be as huge of a deal but think about the concept of.

 

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Ethan Post: A no code approach to bringing additional data right so i'm not going to write a single line of code here i'm going to go through this wizard to go ahead and pull in our context table.

 

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Ethan Post: right with all at one field that we identified on that that first dashboard and i'm just going to pull it in you in quarter.

 

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Ethan Post: Now the other thing I have at my fingertips, is the concept that I already know the joint between these two tables because I leverage that internal some of the reporting that we built for technical teams to determine that there's a field in here called primary contact ID I believe.

 

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Ethan Post: That just joins out to this field here called contact ID my context.

 

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Ethan Post: Okay, so in you know, probably five or six clicks of a mouse, I have not gone ahead and add to that context table I joined it out to my existing customer table and the last thing i'm going to need to do here is go ahead and load our context table.

 

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Ethan Post: With data right.

 

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Ethan Post: So now, and you know, a couple minutes we've extended upon this kind of delivered in quarter blueprint.

 

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Ethan Post: And the idea here is, you know i'll kind of stick with this theme of the IT team has kind of the behind the scenes magicians right.

 

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Ethan Post: Think about that data warehousing process and what you'd have to do to bring that data through the various steps in the chain.

 

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Ethan Post: Within coordinates it's a couple of easy clicks of a mouse, and because of the fact that all we're really doing is connecting out to a source system like netsuite directly.

 

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Ethan Post: I can pull that table in exactly as it exists join it out to my customer data.

 

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Ethan Post: And all of a sudden now, if I can find that contact table right so now, I have this joining you that gives me the ability to extend anything inside my blueprint with now contact information for a given customer.

 

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Ethan Post: So let's take another you know another example of what that actually looks like in the field.

 

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Ethan Post: Right, so I come out to the same dashboard and all of a sudden, I can update this orders by customer with new key contact information so i'll just go out to that.

 

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Ethan Post: That schema that we just identified and pull in addition to my customer table pulling contacts and maybe I want to just go ahead and.

 

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Ethan Post: Look at that particular table right, so I can pull on any of these fields that I want to write email, fax so on and so forth.

 

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Ethan Post: What I can do i'm just going to search for name here real quick just to make it easier on myself.

 

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Ethan Post: And pulling the contact me so we're going to find out to say not every account, not every customer actually has a contact, but for those that do have a primary contact listed.

 

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Ethan Post: i'm now giving my end users, the ability to extend that kind of pre built dashboard into something that might be more useful for them right.

 

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Ethan Post: So there's obviously practical applications this, but the idea here, especially the value for our technical team.

 

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Ethan Post: Is you're not going through you know months of requirements gathering in terms of hey let's let's bake in all of the end users use cases that we have or might need to fulfill.

 

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Ethan Post: and building that into ones in kind of like a one shot approach, so this is very eXtensible super configurable and we've given you kind of all the tools, you need to identify what's here what's not here and how easy, is it to add so that's kind of the first level of complexity right.

 

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Ethan Post: The next thing that might happen, say, the next day you come to your office and you're getting a phone call from you know sales territory manager saying hey.

 

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Ethan Post: This blueprint is great, it gives me access to all the information I need, but my sales team doesn't need access to say you know the worldwide view of revenue right So if I go to this revenue summary dashboard.

 

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Ethan Post: Basically, anyone out of the box is going to be able to see things like global sales across the whole organization right so then include sales for US, Canada and then even parts of Europe.

 

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Ethan Post: So your sales territory manager might say look, I want to lock this data down I don't want to an individual sales REP to be able to see anything outside of their own accounts.

 

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Ethan Post: And according to brian's point is specifically tailored to allow that to think of the concept of pulling the next week data, indirectly, as it exists inside that source system gives us the ability to finally manage how that security is actually portrayed within corner.

 

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Ethan Post: So i'm just going to take you know one quick step to go back to those some of those system tables.

 

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Ethan Post: And one other thing we've done is actually just pulled in the user roles information tables so obviously netsuite has a ton of these right.

 

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Ethan Post: The idea is inside netsuite proper you map a user to a role and each role has specific permissions whether that's by subsidiary department company.

 

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Ethan Post: In the case of a sales REP you actually can even lock that down by particular customer account.

 

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Ethan Post: down to the level Okay, I want to make sure any sales REP can only see his or her activity right so i'm going to stick with that that top REP So if you.

 

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Ethan Post: had seen inside of that that dashboard I just brought up our top REP here corporate is Mary running.

 

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Ethan Post: So i'm gonna use her as a quick example and say okay well she has one role here 1005, which is an inside sales representative.

 

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Ethan Post: So I can come down here and see all the entities that that Mary might have access to if I wanted to I can even build that content for things like subsidiaries departments and so on.

 

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Ethan Post: But for this particular use case right i've had a sales manager come on here and say, I only want Mary ready to have access to the accounts are the customers that she supports so it's pretty simple right.

 

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Ethan Post: i've taken this concept of on a customer table you have basically the sales REP who supports them so i'll go back out to my my entity schema and i'm just going to pull in here a couple quick fields, from our customer team so.

 

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Ethan Post: So i'm going to pull in my company name i'll also pull in my.

 

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Ethan Post: Sales REP ID for my sales are cable and what you're basically going to see it as well, so I don't feel.

 

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Ethan Post: Appalling sales REP ID from the customer table and for any sales REP basically there are assigned to a specific set of customers right so Mary running happens actually sales REP 1008.

 

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Ethan Post: So what i'll do here really quickly is just pull in Mary readings data only and here's basically you know the.

 

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Ethan Post: The list of customers that Mary should be able to see right so there's 204 customers that she is listed as the kind of the direct sales REP on.

 

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Ethan Post: And all I really done is that okay well taking this information, I have an employee table which lists Mary writing in her employee ID.

 

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Ethan Post: I have a sales REP table which lists companies, as well as the REP responsible, so all i've done at the transaction line level, and this is going to be important to understand is i've applied to filter that basically goes through, and.

 

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Ethan Post: and identifies for each transaction of the transaction line level i'm going to go ahead and say okay well on the front end and quarter, basically, what I want to do is.

 

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Ethan Post: filters sales REP ID by a filter that i've defined here is a variable so Mary reading logs into a quarter.

 

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Ethan Post: She sees that that sales REP filter is 1008 meaning she can only see customers that have sales REP 1008 as kind of their their primary sales REP right, so all that to say if I go ahead and kind of impersonate me reading here on the front end.

 

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Ethan Post: i'll go back out to that encoded dashboard here pretty quickly we'll see not the population of data that everyone else can see i'm gonna go back to our revenue summary dashboard.

 

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Ethan Post: And we're going to see kind of a more i'd say you know sporadic view of the data that's represented here right So if I look at sales.

 

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Ethan Post: Right now, no sales in Canada, because mayor REP doesn't support any accounts and Canada, and you basically have kind of a you know, a pretty.

 

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Ethan Post: Well, distributed customer list throughout the us a few more in California, then across the rest of the United States, but you know basically i'm looking at the city level.

 

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Ethan Post: accounts that that Mary reading supports and the cool thing is, you know.

 

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Ethan Post: As long as your end users are aware of this, you know that that functionality, is going to carry through from netsuite So the idea is anything they can see in netsuite they can also see any quarter.

 

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Ethan Post: But they're almost going to be used to kind of seeing this slice of the world anyway right so Mary reading is only looking at about $5 million of revenue coming in.

 

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Ethan Post: Throughout time for the account so she supports and that's kind of the idea right here's all the customers, or maybe reading supports are actually revenue generating which is 118.

 

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Ethan Post: But if I go out to kind of again the population view what you're going to see for anyone that's not listed as a sales REP or doesn't have that same level security applied.

 

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Ethan Post: All of a sudden you're getting kind of that population level right.

 

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Ethan Post: So that's kind of the idea of not baking on this complex concept of okay now we've understood how we can kind of extending configure the blueprint.

 

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Ethan Post: For an IT team, you also need to understand the view work data governance and data security, which included just inherits directly from that source system.

 

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Ethan Post: Right, so making it super easy to not have to maintain two separate sets of transaction level security.

 

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Ethan Post: And the last kind of piece of complexity that out i'll bake on top of years basically.

 

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Ethan Post: The magician's trick of basically for me data out of thin air right so netsuite proper so i'll kind of stick with the theme of a sales order that Brian mentioned.

 

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Ethan Post: So if I have a sales order and i'm an organization, who does things like you know, quoting or has sales orders that are.

 

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Ethan Post: entered well in advance, there can be a lot of variability from the time of sales orders entered to the time that we actually receive you know revenue from that sales order.

 

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Ethan Post: So the idea here is, I hear from a lot of organization to say hey it'd be great to be able to track changes over time, this also obviously applies to things like inventory levels or.

 

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Ethan Post: master data so tracking slowly changing dimensions on things like customers employees and the like.

 

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Ethan Post: But i'm going to do is walk us through a really quick example of how easy it is to do that inside corner.

 

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Ethan Post: So I kind of showed you all the based you know transaction level data that we can pull into in quarter.

 

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Ethan Post: But I have another schema here called transaction snapshot and i've done a couple things to kind of illustrate the various ways in which this can be done.

 

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Ethan Post: But the idea here is, we have a transaction table and a transaction lines table and i'll just stick with the example of transaction lines here.

 

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Ethan Post: The idea is in quarter can load data incrementally from netsuite meaning basically every time you load the schema it's going to reach out to netsuite and look at that transaction lines table inside netsuite.

 

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Ethan Post: And look at the last last modified date to determine what changes have been made since the last time that data was loaded in quarter right.

 

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Ethan Post: So the implications of that are I can set a key here it's basically that last modified date, plus the actual record level key.

 

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Ethan Post: For that record inside of netsuite so What this means is rather than actually updating the data as you would see in netsuite as a source system.

 

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Ethan Post: We can actually insert records based on changes so now, if you have a sales order and update that sales order you'll not see two separate records for the same transaction line from that same transaction.

 

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Ethan Post: Now, again, the implications of this are pretty awesome because what you allow incorporated you is kind of assume that responsibility that a traditional data warehouse would have to take.

 

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Ethan Post: But cut out the you know six to seven months of building and who knows how much spend in order to actually get that up and running and fully tested.

 

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Ethan Post: The other concept here is this concept of dense snapshot and.

 

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Ethan Post: So while you may want to you know for something like sales orders which have the potential to change over time.

 

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Ethan Post: If you think of something like inventory levels right maybe you want a daily snapshot of inventory levels, regardless of it, they changed or not.

 

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Ethan Post: So this concept of a dense snapshot i'll just cover really, really quickly is also key to understand.

 

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Ethan Post: In saying now i'm not looking at that last modified date i'm actually keying off assistant, which says every single time I load this table basically take the population, the entire set of transaction lines.

 

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Ethan Post: And append them to the bottom right, so this is a bowl insert of that every single time that tables run so i'll give you a quick example of how this actually works in the one right so i'll go into netsuite proper and i'll look for.

 

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Ethan Post: A specific orbs.

 

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Ethan Post: Specific sales order so I have a sales order here those place to 3am.

 

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Ethan Post: I think in a second year will see that this is a sales order this pending approval right so it's still in the approval process not yet finalized meaning at any given point I can come in here, and I can actually edit quantities.

 

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Ethan Post: So there's three items on the sales order and there's kind of a set amount of quantity that was created when the sales order was first put in place, but maybe for whatever reason, you know.

 

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Ethan Post: The sales REP on this on this deal wants to come out and maybe reading actually didn't sell five units of this particular item she actually went out and sold.

 

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Ethan Post: Maybe 25 right, so we can update those those quantities and I can save the sales order and again the concept behind the scenes is.

 

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Ethan Post: Now that I made that change to brian's point you know I can take a look at this this audit trail and say hey here's a change that was made to this transaction, and we can kind of get the total here.

 

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Ethan Post: wouldn't quarter provides you the ability to do is come through and actually load incrementally to get that snapshot right.

 

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Ethan Post: So I kind of talked to what's happening in real time, as I load this data incrementally so obviously a records change in netsuite that specific transaction that we just looked into.

 

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Ethan Post: So at the transaction line in the transactions level.

 

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Ethan Post: we're basically going to append a record for that change transaction and that dense snapshot you're going to see here in a second is going to go from I think right around.

 

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Ethan Post: 150,000 records representing the sum total of transaction lines inside of our netsuite instance to I think something around.

 

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Ethan Post: 300,000 if i'm not mistaken right so 234,000 records right which is 156 times too, so the idea here.

 

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Brian Keare: Is a lot of different ways to kind of.

 

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Ethan Post: manage this concept of snapshots right, so how this actually works on the front end, I think, is what really kind of ties, all this together, because it's the idea of for an end user.

 

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Ethan Post: Now they basically get access to to any one transaction that they want to look into, but I can say okay here's my sales order six or two.

 

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Ethan Post: notice that it's actually been changed, three times inside initially loaded this data right So if I scroll down here I not only get access to that first time that transactions enter in which we're looking at 250 units and about $13,000 worth of.

 

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Ethan Post: You know amount on that sales order to now 175 units representing the 25 and 50 that I just put in which actually brings that up to $25,995 right.

 

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Ethan Post: So, think about the idea being able to turn this over time and doing analysis around okay well if people are updating sales orders your inventory levels of changing.

 

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Ethan Post: Why is that, is there any correlation to changing quantities and sales orders and the ability to close business right.

 

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Ethan Post: So, at the end of the day when a quarter really provides you is a visualization suite that can take this concept of changes over time and give you this trending analysis right.

 

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Ethan Post: So i'm looking particularly at this this item here the CEOs years or two, and I can say okay started at about 250 units went to honored and stated 100 but at the same time i've increased the other.

 

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Ethan Post: The other item quantities on the sales order right so again i'm talking to a technical crowd here and that's a fairly technical talk track.

 

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Ethan Post: But the idea here is taking that basic blueprint that we've kind of talked to three or four times now on these sessions.

 

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Ethan Post: which provides the end users, a lot of flexibility and a lot of functionality, but as an IT organization that concerns always okay that's great but.

 

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Ethan Post: How easy, is it to change how scalable is this, and I think we've seen it's highly configurable based upon your netsuite instance in the specifics of the way you do the business.

 

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Ethan Post: Highly configurable in terms of who gets access to one who can see what data based upon netsuite native security rules.

 

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Ethan Post: And then finally configure configurable and extending that netsuite functionality to say things like inventory sales orders or anything you want to track over time.

 

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Ethan Post: You now get access to actually view in real time, as opposed to having to build some complex solution to handle these challenges.

 

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Ethan Post: So i'll pause there I know that's that's a lot of talking for me and certainly a lot of content to cover in a short amount of time, Brian or phil i'm interested to hear you know your guys thoughts in terms of translating this to the value for technical teams.

 

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Phil Reinhart: sure.

 

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Phil Reinhart: And I mean, I think.

 

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Phil Reinhart: Also, you know that you covered you've covered a lot of different.

 

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Phil Reinhart: Areas that in quotes can be valuable and, at the end of the day, I always go back to you okay how am I going to get how am I going to get top line impact.

 

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Phil Reinhart: Out of this solution like in, especially in a time like this, where you're trying to figure out Okay, how can we pick up dollars in this type of economy.

 

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Phil Reinhart: And, and I think of you know as you're going through the dashboard thing and.

 

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Phil Reinhart: You know I think of Okay, who were who were the or people in my organization or my customers that are going to be making those in the moment decisions.

 

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Phil Reinhart: And, and how What are those decisions what area of the business are those decisions being made, and how are those decisions going to get an impact, you know our top or bottom line and.

 

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Phil Reinhart: And so anyways, I just wanted to maybe just a thought, you know as as you go through all that, like.

 

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Phil Reinhart: You know where do you, is it the executives that are getting the most benefit out of the dashboards is it is it the individual contributor, is it is it, maybe even just directly to the customer, where do you see that you know when the rubber hits the road.

 

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Phil Reinhart: And we've got this implemented like who who's really being impacted.

 

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Brian Keare: From, from my perspective, in my experience at North tech it's it's really you know I ran the it team our it team went overnights.

 

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Brian Keare: from being the folks that you know, we had offices and people would be coming to our offices saying.

 

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Brian Keare: gosh you guys, I asked her this two weeks ago you haven't delivered my ability to report on you know this new dimension that we just.

 

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Brian Keare: lit up or this new system that we just incorporated into our you know that I just gave you into my dashboards and so what's going on.

 

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Brian Keare: We transform that kind of we were the you know the whipping team, or you know, whatever whatever the metaphor is that people got mad at to.

 

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Brian Keare: In many respects we became the heroes, because we were able to achieve a measure of instant gratification and being able to answer much more quickly.

 

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Brian Keare: These challenges and these questions for that came from executives department heads or analysts in the field, and we also empower them.

 

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Brian Keare: To do their work on their own, we were able to say hey you can do a lot of this on your own we set it up, and you can go with it, and do it on your own.

 

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Brian Keare: And that's really a game changer, so I think that you know what it does for the it team is it actually makes you heroes as as opposed to somebody who seems to.

 

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Brian Keare: be getting yelled at all the time, and you have to juggle competing priorities, but you know one thing i'd love to redirect to ethan is.

 

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Brian Keare: You know, one of the things that we haven't touched about advanced analytics are the ability to move from.

 

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Brian Keare: To add on to the operational analytic framework that we've talked about today and we've talked about in general and say.

 

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Brian Keare: hey you know I know the buzzwords of predictive analytics I know the buzzwords of machine learning and Ai.

 

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Brian Keare: Is there anything that in court, I could offer that actually gives me the ability to do some of that as easily as we can do some of these operational analytics things that you've done, and you know.

 

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Brian Keare: i'll leave it to you ethan to talk about your experiences I could talk about one nor tech but.

 

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Brian Keare: You know I think that's another thing that I think we can begin to touch on and then continue the conversation with anyone who's interested.

 

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Brian Keare: In exploring that further with us because it's pretty pretty straightforward and easy to accomplish and in quarter, like some of these other things that we've done ethan.

 

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Brian Keare: What are your thoughts so.

 

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Ethan Post: really interesting question, I mean, I think.

 

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Ethan Post: You know the the ml data science spaces is getting so vast that there's a library of tools that are dedicated specifically for that right.

 

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Ethan Post: And every organization, I talked to you, whether they have a team of dedicated data scientist, or whether they're just kind of you know kicking the tires on it will say hey.

 

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Ethan Post: I have kind of this white whale scenario where, if I can figure out this one piece of information, if I can predict who's going to turn.

 

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Ethan Post: it's going to completely change my business.

 

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Ethan Post: The challenge they always have is even if I have the best data scientists know like where do I even get that data from how do I have the capability putting all this data together in one place to answer that question.

 

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Ethan Post: And I think that's what it really brings to the table in terms of data, science and machine learning is.

 

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Ethan Post: This is holistic view of all your business and all your data source so we've talked about netsuite but talk to any of our customers and they're looking at multiple 5678 sources in a single.

 

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Ethan Post: instance, and what that provides you the ability to do is any research you go out to and take a look at.

 

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Ethan Post: 75 to 80% of the time of data scientists spent is wrangling scrubbing data in quarter cuts that out, full stop and says look your data scientists do data science so.

 

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Ethan Post: I think there's a lot of value to be done there, and I mean something i'm particularly interested in is this concept of baking in some of these data science concepts into our blueprint so thinking through.

 

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Ethan Post: Every every Organization has eyes on things like predicting customer churn specifically being able to look at like accounts receivable predict who's going to pay and how long it's going to take.

 

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Ethan Post: and frankly there's some common threads are common themes throughout every organization, I talked to that has the you know the capabilities to do this, and I think.

 

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Ethan Post: that's something I think we're even looking at building out more you know operationalize as part of that blueprint so there's my soapbox I appreciate the question I think it's something i'm obviously pretty passionate about but yeah right i'll see it up to you.

 

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Brian Keare: Great I think that that you know, I think that that hopefully give folks a taste have.

 

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Brian Keare: a taste of how in court, it can change the game for teams that are interested in it analytics advanced analytics and being able to deliver some advanced tools directly to their end users and to empower them.

 

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Brian Keare: So I think i'll leave it to you phil to wrap up to talk about the October value sprints and you know, to reiterate that.

 

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Brian Keare: And I think we've touched we've touched on many of these subjects, I think the good news is that if anybody wants to actually explore these in more detail.

 

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Brian Keare: We don't have to set up a complicated multi month proof of concept.

 

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Brian Keare: You can sign up for your own trial, you can get your own blueprint in your own trial instance, you can connect your own data.

 

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Brian Keare: And within a matter of minutes or hours you can actually start seeing some of your own data inside of encarta in these ways and see for yourself how easy it is to do some of these things so over to you yeah.

 

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Brian Keare: and

 

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Brian Keare: I mean.

 

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Phil Reinhart: Just going off of that right, we have this value sprint and and you know we're not the old school.

 

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Phil Reinhart: Technology company, where you know 21st century here, we want you to try the technology before we ask you to move forward with us and we want you to not just try it and.

 

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Phil Reinhart: Do a proof of concept, but we want you to solve it and get to an outcome in a matter of weeks, and you know we're here to to throw our time and our talent or technology at you all.

 

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Phil Reinhart: To to accomplish that and we want you know the gnarly Harry you know difficult challenge that you think is going to take two years, and you know, like, for example, at one of the largest.

 

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Phil Reinhart: You know, coffee retailers we they had a basically a two year project that we turned into 11 weeks, and in part of that we help them increase some of their food sales and reduce food waste and so there's there is an opportunity here where we're we're taking very long lengthy.

 

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Phil Reinhart: Data initiatives and shortening into to matter weeks and we're here to make that happen and value sprint I mean that's really that's the core story here.

 

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Phil Reinhart: And so yeah.

 

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Phil Reinhart: Next slide please you think.

 

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Phil Reinhart: The cords a trial is available@cloud.com so we're not you know hiding behind the curtain here, you can go out and try and quarter right now.

 

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Phil Reinhart: And there's no, you know download the S go on your desktop where you have to get an approval from it, you can access in court to directly through your browser and start trying it today.

 

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Phil Reinhart: So it's it's right there, and you can you can see the speed that we've been talking about and upload data and give it a go, and this is something that you can do without even contacting us.

 

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Phil Reinhart: You know you don't need to call you know me a sales guy or even a you know, a sales engineer, you can you can get going yourself give it a try.

 

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Phil Reinhart: All the sessions from the four from the series are going to be available all the recordings, so you can access those right there in the link that we've posted and then.

 

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Phil Reinhart: And that's presented, I think it's less I know that's it Oh, and then just a reminder yeah just a reminder invite your peers to watch the recordings we've got the.

 

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Phil Reinhart: This series out there, we have the value sprint available to to you and your peers your colleagues and connect with us, we want to talk so anyways Thank you so much, everybody for attending this series, and we look forward to.

 

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Phil Reinhart: talking with you and solving some of these use cases.

 

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Phil Reinhart: Any any questions, I think we we got four minutes yeah questions that might be out there.

 

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Phil Reinhart: I did have I wanted to kind of follow up on the.

 

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Phil Reinhart: The conversation you guys are having around the time value of data and just wanted to make a mention that.

 

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Phil Reinhart: I i've seen a couple studies come out one from Harvard about how the time value of data is is very much.

 

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Phil Reinhart: A critical piece of your Ai and machine learning models and if you're not getting the data.

 

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Phil Reinhart: To the models fast enough, and if you're not getting enough of the data to the models fast not fast enough just historically and the current moment data your models that you've invested maybe you know, three or four data.

 

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Phil Reinhart: Scientists to build over the last six months aren't going to produce the outcomes that you sought to see you know.

 

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Phil Reinhart: To.

 

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Brian Keare: Go after and so.

 

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Phil Reinhart: I think that's a key very important factor is like it costs so much take so much time to get there and then.

 

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Phil Reinhart: All of a sudden, you know you're you're not able to get the data to those models fast enough or you're not in a you're not able to get down to that that detailed level for those models to matter.

 

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Phil Reinhart: So I just wanted to point that out it's it's I think you know coming from the all tricks world and some other diet data science worlds, you know before all in court to that really speaks to me.

 

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Ethan Post: So yeah.

 

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Brian Keare: Good point I just ECHO ethan's comment, which is that you've already got all that data, you know real time operational data inside of in quarter and instead of having to.

 

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Brian Keare: Have a project that offloads that for use elsewhere, the philosophy of in quarter is make that same data available to data scientists to anybody who needs it.

 

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Brian Keare: And it's easy to understand, easy to use, you don't need to flatten it you don't need to shape it grab it as it is and do your analytics on top of it do your ml Ai.

 

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Brian Keare: predictive analytics on top of it, in addition to your operational analytics and so it's always there you don't need to.

 

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Brian Keare: You don't need to have success of projects, and so, if you want to go back and test your model you take the data or.

 

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Brian Keare: You know, a portion of subset of the data to your do your modeling on and then you go and do your regression testing against the rest of the data.

 

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Brian Keare: Inside of encoded validate your model from an operational perspective, so the cycle times of being able to create models and then go back and test them against actual data those cycle times are super quick so for folks who want to get into the advanced analytics portion of things.

 

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Phil Reinhart: You see a lot of data science tools out there, I mean what does that look like mean if i'm doing something in SAS or did briggs or all tricks, or you know data IQ you know name your data science tool How does that work with all this.

 

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Brian Keare: yeah.

 

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Brian Keare: I think we're at time that might be, it might be a big question for another day we're going to get in that one, I think.

 

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Brian Keare: phil and say you know, for those of you who want to dive down into that I think we're scratching the surface, but those are really great questions, and you know we'd love to talk to anybody about about them, so thank you.

 

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Brian Keare: You know, thank the person in the audience for that question, but I think we'll you know not not.

 

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Brian Keare: We would love to talk to you further about it just contact any one of us, and we can show you a little bit show show you around the quarter platform and show you what we can do in that respect awesome.

 

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Phil Reinhart: Alright guys well have a great day.

 

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Phil Reinhart: And thank you for attending.

 

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Thanks cheers.