Modern Data Warehousing Analytics without the Modeling

It’s time to rethink your approach to data warehouse analytics

It’s impossible to account for every question that a business user might ask their data warehouse. This is a big problem — when users ask a question that hasn’t been modeled in the data warehouse, the time and resources it takes to find a satisfactory answer often outweigh the benefit.

Modern data warehouse analytics, however, requires the ability to quickly provide insights to ad hoc queries. Fortunately, technology solutions exist that can support these new data warehouse analytic needs. 

In our research paper, Modern Data Warehousing Analytics without the Modeling, Wayne Eckerson of the Eckerson Group investigates these new technologies and how they can support modern data warehousing. In it, Eckerson discusses:

  • Organizations that have implemented big data platforms running on Hadoop and Spark to enable scalability, speed deployment and accelerate insights
  • In-memory solutions designed to speed query performance and work in concert with disk-based solutions
  • New data mapping algorithms that automate model design and convert complex operational data into query-able objects and views

 

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