A concise tour of one of the basic components of Kimball dimensional data modeling. We explore the three types of fact tables, and then analyze why they have lasted the test of time.
Most data practitioners I talked to agree on two things. * We need an abstraction layer to define metrics consistently and rigorously. * We …
Ralph Kimball's classic book The Data Warehouse Toolkit introduce the world to the practice of data modeling. Here's how to read it in 2022.
In our third and final part on Agile Data Warehouse, we take a look at the origins of the Agile Manifesto, from which Corr and Stagnitto took inspiration.
The second part of our series on Agile Data Warehouse Design, a 2011 attempt at applying the principles of agile to the practice of data modeling.
Agile Data Warehouse Design is a 2011 attempt at applying the principles of agile to the practice of data modeling. This is the first post in a series on the ideas from the book.
What a new approach to slowly changing dimensions tell us about the future of dimensional data modeling.
There's a tendency for people to conflate OLAP with OLAP cube. We take a quick look at how this happens, why it shouldn't, and why it matters if you're a data practitioner.
A definitive history of the rise of the OLAP cube, how it's affected our industry, and what comes after.
Holistics's data modeling layer allows data teams to radically increase their productivity. No repeated queries. Self-serve reports and dashboards. Here's how it works.
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