November Action on Insights
As the sheer volume of data continues to explode within organizations, the practice of effectively visualizing and interpreting data is becoming an increasingly critical skill to success. In this session, learn how to enhance your ability to design and tell a story with your data using best practices in the Incorta platform.
Watch this webinar to learn:
- Understand the critical role of data visualization in organizations today
- Learn about the information design process
- Basic design principles for legibility and accessibility
- Bringing high-level views vs detail views together with drill downs
Mo El Jaafari
Cara Immel: i’d like to welcome everybody to november’s action on insights This is our monthly webinar series where we’re sharing best practices and tips and tricks.
Cara Immel: To help our customers unlock the full potential before this direct data platform today we’re going to dive into dashboard designing principles in the quarter platform, my name is carrie i’m all i’m a senior manager on the customer success team here and or.
Cara Immel: In quarter and i’ll be your host today so we’re going to do dashboard design principles and.
Cara Immel: What I like to do is before we jump in introduce myself, and so, if you were to import a.
Cara Immel: I have experienced with the largest financial firms around the real estate pharmaceuticals, etc, and really excited to be here at in quarter.
Cara Immel: And then mo will you go ahead and introduce yourself.
El Jaafari: Yes, thank you so Hello everyone, my name is George safari and part of the solutions, but with that incorporates a working as a solutions architect with our customers in India, I started my career as an analyst so I i’ve got access to all the bands of.
El Jaafari: Finding data trying to analyze data and trying to make some sense of it, and after actually my stuff as an analyst I moved to the vendors working more on the solutions, so I would be very happy to share with you today my thoughts on.
El Jaafari: dashboard then and yeah the benefits of visualizing angel.
Cara Immel: Excellent Thank you so before we get started i’m sure you have lots of questions or even some commentary that you’d like to bake as we’re going through.
Cara Immel: If you could keep your questions that you would like to address to mo in the Q amp a box it’s really helpful to keep them.
Cara Immel: Keep it separate from just comment commentary that are in the chat window so at the bottom of your zoom screen, you should see the Q amp a.
Cara Immel: Please put any questions in there and we’ll leave some time at the end to address those if you just have want to give shout outs or hey that’s really super cool.
Cara Immel: commentary to mo and to myself, please put that in the chat window and so without any further ado i’d like to turn this over to Joe and we’ll go ahead and get started.
Cara Immel: So i’m going to stop sharing and know if you’d like to take over if that’s okay.
El Jaafari: yeah that’s perfect Thank you Kara and i’ll be sharing my screen.
El Jaafari: And please let me know when you can see it.
Cara Immel: I can see it.
El Jaafari: Perfect so thank you again everyone for attending our session today, so our goal today would be to look at the.
El Jaafari: dashboard in general and visual analytics our goal is to allow you to see.
El Jaafari: The to enhance your ability to design and the stories using your data so we’re going to start by looking at why we’re talking about visual visualization in general, then we’re going to.
El Jaafari: See actually how that whole process of information design happens and we’re going to go through like some design principles and.
El Jaafari: That make actually dashboards and reports your grading easier to read for broader audience and how as well to bring a high level and detailed information in one place.
El Jaafari: Before actually we get started, I think, an important question that we need to our to ask is what are two visual effects, why are we talking about visualizations in general and visual analytics.
El Jaafari: One of my favorite quotes trying to describe the importance of issue this is this one actually from Stephen view which actually wrote lots of books.
El Jaafari: On visualizations in general and and analytics so he said he one of his books that numbers have an important story to tell they rely on you to give them a clear on convincing voice.
El Jaafari: We all actually have to deal with data we all have to deal with numbers and it’s actually up to how we represent, that information and.
El Jaafari: share that information with our our audiences our users that actually actions can be taken and important steps can be made so that’s what we’re going to do today.
El Jaafari: we’re going to see actually what numbers can tell us today and then we’re going to see what’s the best way to represent those numbers and why actually we need to start thinking about those.
El Jaafari: And, of course, the best place to see that would be in the integrated platform, so I will run actually the session today almost as a DEMO so we’re going to look at.
El Jaafari: lots of different concepts within the equal part for that that way, actually, we can see how the platform can help us see and understand our data data.
El Jaafari: So I can select the numbers of important story to tell us what we’re talking about the visualizations and their importance it all actually narrows down to.
El Jaafari: The speed at which we can understand the data that is in front of us, and therefore the speed at which we can take actions against actually the data that we’re looking at.
El Jaafari: You may be wondering why actually we need to think about visualization is you know what addition do visualizations bring.
El Jaafari: let’s imagine that we’re looking at the table, where we just have a list of numbers, in our case here we’ve got a table with five colors and a Trolls so 14 members in total.
El Jaafari: And we were tasked actually to count the nines within this table so just actually give you a few seconds, and there is a ball, that will be.
El Jaafari: appearing on use alternative, you can just actually answer as quickly as possible, how many knives can you count in that they will so just actually give you a few seconds to see actually what the different answers that we get our.
El Jaafari: So you can just actually select that answer and click on submit.
El Jaafari: Some shots, you will have seen a lot of different results, some of you may have.
El Jaafari: noticed 789 so thinking actually about the same exercise that we have done.
El Jaafari: we’ve actually will give us exactly the same table by now actually we color coded those lines and we’ll ask exactly the same question.
El Jaafari: to count how many number Nice we see in the table so there’s gonna be like a lot of balls and now you’re actually interested in seeing how many people actually are going to get the answer correct.
El Jaafari: So you guys actually or all of you actually gets the right answer this time, which is eight lines and.
El Jaafari: All of you actually as well, have answered a lot quicker than you have in the in the previous exercise, so you were able to actually count the number nine a lot quicker than, then you were actually asked before so everyone actually was able to answer, quite correctly, on the on.
El Jaafari: The on the question itself and that’s actually due to the fact that now the numbers are color coded in a way that makes it easier for them to stand out.
El Jaafari: You may actually look at or start reading the numbers vertically horizontally, regardless of which one can easily spot those number nine.
El Jaafari: You may be actually wondering that first of all, they will it doesn’t really matter at the end of the day, you would have gotten the right.
El Jaafari: The the correct number, even if it took you a little longer, but what if actually will have to deal with a larger data set.
El Jaafari: If actually we’re looking at at one numbers at the same time hundred numbers at the same time, and so this is really what is important to simplify the data region step for our end users and ensure that actually they can take quick actions based on data that that is in front of them.
El Jaafari: We take actions, a lot quicker when we can see the data so imagine actually we are managing.
El Jaafari: data related to production for a chain of supermarkets we’ve got our sunrise view here where we’re looking at our different products and how much we have sold how much profit, we have.
El Jaafari: gotten from each of those products across all our seconds, if we were actually tasked to look at all of these categories and decide which ones which one is the least profitable, it will actually take us some time to be able to.
El Jaafari: To to recognize actually which one it is, but what actually if we changed our approach and our way of looking at the data.
El Jaafari: What if we added actually some of those cognitive elements into into the data itself so let’s say, for example, we can add some conditional formatting and highlight all of those that are.
El Jaafari: below zero, for example, changing the color for those so now actually instead of going through all of the table we’ve only got five figures to look at and then the decision can easily be made.
El Jaafari: But what is actually our manager is asking us about the product category that is the most profitable, as a follow up question, this is where, again, we will need to find another way to.
El Jaafari: Look at the information, and so, so we should always actually be taking in consideration the questions that the end users are going to be asking.
El Jaafari: When sharing a dashboard and report with those end users, there are a lot of different visual ways that could actually make answering all of those questions, a lot easier and a lot simpler.
El Jaafari: And therefore, for example, looking at our data as multiple colors can actually help us simplify that so we can actually be looking at all of our different.
El Jaafari: subcategories across all the different segments and highlighting which ones among those are the least, and the most profitable representing the data in a graphical way makes it easier for us to easily spot.
El Jaafari: Like relationships within our data trends within our data and easily take actions based on the data that is in front of us.
El Jaafari: So always think about what actually the questions, what are the questions that the end users are asking, but as well, those questions, what are the.
El Jaafari: The other questions that they that they will trigger and, therefore, how can we share with those users data in a certain way, that it would allow them to answer all of their concerns and therefore take actions based on that data.
El Jaafari: I usually actually like to go through the ask on Quartet i’m not sure if everyone is familiar, but this is a really good use case.
El Jaafari: To highlight the importance of visualizations enjoy imagine actually that we have.
El Jaafari: One data set we’re actually we’re looking at four different regions so we’ve got region number one number two number three and number four.
El Jaafari: within each of these regions we’re tracking multiple stores so 10 stores for each of them we’ve got two different variables so X and y that would be like the sale sales and profit.
El Jaafari: or says that costs or any other metrics that we may be tracking so let’s actually go the X ourselves and the way our prophet.
El Jaafari: Looking at the data table we’re not really noticing anything we don’t really know or, this is actually not triggering any actions we may be.
El Jaafari: Like interested in in analyzing our data in a statistical way, but actually what we notice when we are looking at the average X our average sales is the same across all the different regions.
El Jaafari: The variance for that same variable is the same across all the different regions, looking at the average of the second Bible so of the why.
El Jaafari: it’s exactly the same across all the different regions, the violence as well, is the same trying to build a tree regression block we’ve got exactly the same intercept and slow.
El Jaafari: across all the different regions and the correlation between the X and the y is almost the same across all the different regions.
El Jaafari: In fact, actually, while we’re building that regression model for our data we’re getting exactly the same drive across all the different regions so looking at this data, we may be actually.
El Jaafari: inclined to say that the operations within all of those regions were exactly the same, and the results actually that were obtained in those regions are exactly the same.
El Jaafari: by looking at that same data in a more visual way may actually throw some new conclusions that we may not have seen before.
El Jaafari: Looking at, for example, our fourth group, so our fourth region we noticed that there was an outlier in that region of.
El Jaafari: store that has performed a lot that has generated more profit, while selling the same as many other cells within the same region and therefore that’s maybe one lesson, as we learn.
El Jaafari: We notice that the amongst all by all like by all the stores in region for was exactly the same, except for one store one outlier and therefore that’s maybe another.
El Jaafari: lesson to learn, so there are actually a lot of conclusions that could be drawn on the data on the data itself by just actually looking at it in a more visual way and represented in visually in a photo of us, and this is why it is important to additionally.
El Jaafari: analyze the data in a statistical way in a best best way to focus as well or visualizing it and, seeing that data live in front of us and interacting with it.
El Jaafari: When we’re talking about visual elements, there are there are actually like there are multiple elements that we notice when we’re looking at data.
El Jaafari: So we’ve like as humans we’ve got a tendency to notice actually lens, and this is really important, when comparing quantitative data position as well, so if they they scattered around a certain graph we can easily spot the position of different boys within that graph.
El Jaafari: With good be.
El Jaafari: A good a good element as well to add, especially if we’re going to make some numbers bold when we when we achieve a certain target and so on.
El Jaafari: size, as well as an element element that we notice and therefore an appoint that these are the different sides of the other points may stand out for us intensity and change of color and blue, as well as we can easily see within within points.
El Jaafari: When we’re dealing with non quantitative data, so if one.
El Jaafari: shape is oriented differently than others or is completely different than others, or is it close with other or or with a mark added those are elements as well again that we know this easily with our eyes and, therefore, those are the kind of stand out for us when looking at data.
El Jaafari: And this different.
El Jaafari: elements.
El Jaafari: highlight can be utilized for different types of data, so when we’re talking about data, there are three types of data that we’re dealing with.
El Jaafari: we’ve got qualitative data so as well as we called categorical four dimensions these could be country names, for example, names of people types of drinks and so on.
El Jaafari: And the way we perceive those usually is either by the position of the point within the graph different using different shapes or different colors for different categories.
El Jaafari: When dealing with qualitative and with qualitative data.
El Jaafari: But, but where there is an order, where there is where there is like a ranking, for example, going from goals two wrongs going from excellent to poor or from loving it to hating it, as also where there is an order to the different.
El Jaafari: different categories that are set, then again position can be utilized by size, as well as a good element corner and density can help us identify.
El Jaafari: One one category or the other, or actually using different colors different shapes so use it for example go look out for gold and so on.
El Jaafari: And when dealing actually with quantitative data So these are continuous information and measures that we have in our data, then we are able, actually to.
El Jaafari: To spot positions again so position of a point within our graph land when dealing with bars, for example, size when dealing with buys and other element or word when dealing with bubbles and color intensity we’re going to see some example of these throughout the presentation.
El Jaafari: So let’s look at actually some examples and see as well, like how we can sometimes make the girls that we’re working on that so looking at the graph here, where we are looking at the results from the last Olympics and the middle is obtained by different countries.
El Jaafari: We are actually able, with this graph to easily get all the countries rank but actually this graph could be made a lot better by making some changes into it.
El Jaafari: So, looking at this graph, for example, just the fact of changing the orientation can help us actually easily read the data.
El Jaafari: So just changing the orientation has made me actually has made it easier for me to to recognize the different countries that have obtained the medal in the Olympics and the ranking as well.
El Jaafari: In our case, we actually were looking at like more than 50 countries, but are we really interested in that many maybe we just want to see those countries that have that have achieved.
El Jaafari: higher than a certain threshold that we have in place, so we just want to see countries that have obtained more than 5050 medals.
El Jaafari: And that’s very easy to achieve and therefore would make the view more relevant in case actually we just looking at the top five the top 10 among our data set.
El Jaafari: This is really where the our our main concern should be the end users, what are they going to be trying to draw from the data itself and therefore.
El Jaafari: making sure that the visual doesn’t doesn’t overwhelm them that we’re not putting too much information with individual, but actually we’re putting the information that those users would be interested in.
El Jaafari: When didn’t actually with the quantitative data so in our case here we’re looking at listings or on airbnb like four different neighborhoods in the UK different types of floods.
El Jaafari: I mean we are looking at the average price that those actually cost, but we cannot really draw any information we get actually lost in the table, we look at 122 roles that we may not be able to.
El Jaafari: easily easily read through but just actually thinking of better way to visualize the data may make our analysis better manually think of building a heat map, for example, highlight in.
El Jaafari: The neighborhoods where where where the the the listings are the most expensive on average.
El Jaafari: Actually, will notice in that in the City of London renting a hotel room is more expensive than renting an entire home, and this is really insane this is type of insight that.
El Jaafari: We may not we may have missed actually just looking at the whole data table, but is easily spotted when representing the data in a certain way.
El Jaafari: We can easily see as well all the places were renting a hotel room maybe cheaper and therefore.
El Jaafari: We could actually consider, for whatever actually we we travel to the UK and or we travel to London and so on, so just actually thinking about ways to represent the data may actually the data, the data points that we will stand out may make reading reading certainly visual a lot easier.
El Jaafari: We shouldn’t forget as well that us humans cannot read more than eight colors so just actually presenting all of the information in multiple colors they get us actually lost trying to read the data.
El Jaafari: Thinking about ways to minimize the those those those colors can help, so we can actually instead of looking at every single subcategory as one different color think about group in that group into subcategories into a group in those categories and subcategories by.
El Jaafari: grouping those subcategories by the category that they belong to, and therefore now we can easily see all the technology products, the furniture products and the Office supplies for that and we see the share of each of those products.
El Jaafari: Within like our total sales so always thinking about minimizing the number of colors because the fact of having too many colors in a graph makes actually that color element.
El Jaafari: Like less useful and it will be.
El Jaafari: don’t forget as well, but the way color is perceived.
El Jaafari: is relative and therefore what some people can see us light Gray would actually be the same Gray, if the background was later so always taking consideration that multiple elements could influence how people see a certain color or thoughts or miss it.
El Jaafari: And that, as well, some of the people that are going to cause you the information that we have in front of us may not see the color the same way that we do so lots of people do have.
El Jaafari: conditions that prevent them from seeing the colors in the same way as everyone else.
El Jaafari: And therefore we should actually be, we should make sure, actually, that the visual that we’re building is consistent with those users as well.
El Jaafari: Therefore he, for example, green and red will be seeing the same for someone that’s that that has brought along with blind.
El Jaafari: would be seen, the same as well for someone that that that has deter rokia and so on, so always.
El Jaafari: Think about using if, in case actually color really matters, and we want to distinguish between different colors to use colors that wouldn’t be seen as the same by other users and there are actually websites online that help you.
El Jaafari: To see what would be the best color too much a certain color that you’re using in your above.
El Jaafari: So, looking at this view that we have in front of us when we look at our total sales and the type of shipping the shipping method that was utilized this actually how we, we see it.
El Jaafari: Someone with the the duty Renault would see it actually differently, and therefore they may not actually be able to to.
El Jaafari: To see a difference between the first class and same day, I mean in quarter, we can actually highlight those but just looking at the graph for for the won’t be actually able to.
El Jaafari: see the difference between those two different colors while in our original graph the difference seeing very clear.
El Jaafari: Another important element we’re looking at the analytics as G geographical data so whenever actually we are whenever actually location matters, the best thing to do is to use.
El Jaafari: To use a map to represent that as actually we can easily see in our case here for the airbnb listings where all the expensive locations are.
El Jaafari: geospatial element doesn’t have to be coordinate doesn’t have to be like a point with luggage allotted you, it could be state names country names and so on.
El Jaafari: But we shouldn’t be using maps just because we can use maps, so in my case here i’m looking at actually the medals obtained by different countries, I can represent that information as much, but this actually not.
El Jaafari: Bringing me any insight the geographical elements of the location of the country doesn’t really matter when it comes to the number of the metals or update and therefore presenting the information as.
El Jaafari: A bar charts, for example, would be more relevant or as a table, for example, in case my users need to consume it in a different way and so on, so always think about what would.
El Jaafari: What would actually be end users gain from this insight before before actually choosing the type of insight that they go for.
El Jaafari: In fact, actually when we’re dealing with the visual analytics there is a whole.
El Jaafari: process that goes in place so from the tasks are from the first question that we have.
El Jaafari: to really be able to act and share and it’s actually a circular process that incorporates year as well to help you with at all the steps so from.
El Jaafari: The point of getting your data finding that structure within your data viewing the data, developing the insights and sharing that insight with with the users.
El Jaafari: it’s it’s as well the cycle that continuously into like where the different perspectives to interact with the other, and that is never ending in a way, as actually answering some questions will will will make you actually asked it a mo.
Cara Immel: mo we are just about up.
Cara Immel: on time.
Cara Immel: That while that was perfect.
Cara Immel: That was fascinating Thank you so much for sharing all of that, if you have any questions for mo if you want to go a little deeper I know we’re at the bottom of the hour, but we can hang on for a few more minutes if you do have any questions, I do have one question from mark.
Cara Immel: The pre attentive elements tab which was, I believe it was the grid that talked about.
Cara Immel: The different types of.
Cara Immel: Qualitative categorical or quantitative john he asked is that an rts insight.
Cara Immel: And I won’t let you answer that.
El Jaafari: i’m not i’m not really sure so make Actually, this is a question that I can come back and send an email.
Cara Immel: yeah I think.
El Jaafari: We take a note yeah.
Cara Immel: yeah if I if I, if I understand what mark is asking, I think, is, I did you basically have an image inserted into that.
El Jaafari: yeah yeah exactly.
Cara Immel: um and another question that we have from ashwin, how can we create an org chart with two levels of hierarchy first level one to one, while the second level, maybe one too many example director manager individual contributors.
El Jaafari: yeah, so there is actually the archetype of.
El Jaafari: Of charts of insights within within the quarter and therefore it’s just a matter of having actually that relationship between the different levels of hierarchy so as soon as you have actually the level.
El Jaafari: That you have that relationship between the different levels, you can easily utilize as.
El Jaafari: As a graph type the hierarchy type, so there is that as well, like something that the car is going to go through the day, so there is a lot of additional content that you may benefit from like on our Community website where we’re going actually in details into each of these.
El Jaafari: types of insights and types of graphs that are available in court and a yorkie is nothing yet.
Cara Immel: And that is a great segue if you want to put up the Community tab for us or screen.
Cara Immel: and
Cara Immel: So there we go so want to make sure this would be a great question to post to the Community on make sure you’re registered on the Community and be where you can have.
Cara Immel: Peer to peer discussions you can post your thoughts comments challenges into our format forums to begin interacting and so, even if you’ve connected with someone here today leave on the direct messages as well on there is and.
Cara Immel: And i’m going to go ahead we’ve already posted the link to the Community or to the chat there is also as mark pointed out there’s already a video out there on the Community or actually rather to YouTube and rob has done that he’s one of our.
Cara Immel: Part of the quarter team and has shared great wisdom, and you can again if you have obstacles post those in our Q amp a forums, if you have ideas, how to.
Cara Immel: To improve the platform we’d love to hear your ideas vote up other people’s ideas were listening or monitoring that does help influence our roadmap.
Cara Immel: On there’s best practices articles, we also post all burn learning events, and we have a fantastic knowledge base so speaking of learning events.
Cara Immel: Our December action on insights is going to be coming up, and so let me just pull up that me find the information on that I have so many screens open.
Cara Immel: And so um.
Cara Immel: So if you’ve enjoyed today’s session on, we are going to in December feature and intro to session variables row level and column level security and you can register via this link i’m going to go ahead and drop that into the chat oh looks like i’ve already been beat beat to that.
Cara Immel: And don’t forget the Community and what i’d like to do is thank mo if you could all join me in thanking them Thank you mo for your.
Cara Immel: expertise and sharing your time with us today really appreciate that everybody have a.
Cara Immel: An excellent day and Mike schumer i’m sorry we didn’t get to your question, but i’m going to grab that and we’ll reach out and get you an answer there Thank you everyone have a great rest of your day.
El Jaafari: Take care.