Picking the right data model is one of the most important decisions that senior IT leaders can make. Historically, there were two models to choose from: Ralph Kimball’s “bottom-up” approach to mapping atomic data or Bill Inmon’s “top-down” model. In recent years, however, the technology that supports BI and data warehousing has evolved rapidly. Now, there is a third option for data warehousing and BI in a post-star-schema, post-ETL world: non-dimensional data modeling.
As a follow up to last year’s wildly popular Incorta eBook and webinar, The Death of A Star Schema, we revisit the age-old data modeling debate in our latest eBook: Death of A Star Schema (Redux): Moving Beyond Inmon and Kimball. This time around, we examine the latest breakthrough in data architecture—non-dimensional data modeling—and explore the various ways it outperforms traditional approaches. We also share advice for IT leaders on how to make the vision a reality for their business. Here’s a preview:
Tackling the Unknown Unknowns
A bottom-up approach to data modeling requires many assumptions about the problems you are looking to solve in the business. While this is certainly a useful approach for well-defined problems, disruptive innovation usually lies beyond the domain of the everyday. A top-down approach enables you to answer a much broader set of business questions, but its practical value is limited by performance issues. This model requires data to be pushed to cubes and marts, which slows everything down.
Non-dimensional data modeling, by contrast, overcomes these limitations and opens up the possibility of identifying the unknown unknowns in your business. This allows you company to approach BI in a way that more accurately reflects the real world of business.
Enabling Data Curiosity
As the world of business becomes increasingly digital and interconnected, IT leaders in every industry are starting to recognize that problems are more horizontal than vertical, and that modern BI can tell a broader story about an organization than it ever has before.
Bottom-up data modeling can help you answer specific types of questions with data—many of which are highly valuable—but that’s about it. Top-down data modeling, meanwhile, lacks the speed and agility necessary to keep pace with modern business.
Non-dimensional data modeling improves on both and stands to catalyze a new way of thinking at a company-wide level, completely transforming an organization by laying the groundwork for everyone to become a “data scientist” in their own right.
Evolving IT Team Roles
There are no shortage of IT leaders with shining track records of scoring “quick wins” on data and BI. These short-term victories are important and propel many companies out of the doldrums or into their own golden eras. But the never-ending proliferation of data and its soaring value demand that IT leaders take a long-term view of the data, the company, and the industry.
Download your copy of Death of A Star Schema (Redux): Moving Beyond Inmon and Kimball today to find out how fundamental advances in data technology are giving rise to an entirely new model for data architecture—non-dimensional data modeling—and how to make it work for your business.