Skip to main content


Showing posts from July, 2014

Virtuous Designs for Tabular Data Modelling

Much of the beauty of Microsoft's Tabular model is the apparent ability to escape weeks of star-schema modelling that are common place in OLAP cubes. While tabular can be blazingly fast both to develop models for as well as to use, the performance of the Vertipaq engine varies massively depending on how you present your data to it.

Below are several data modelling patterns you are likely to encounter:

The Monolithic table design involves joining all source tables together into a single denormalized representation. Tabular is able to group / aggregate and filter rows easily in this model, so while care needs to be taken when writing DAX expressions, the resulting cube will perform well.
Easy to get started. Performs well. Cons:
DAX expressions trickier to write. Cube loading times may suffer. Only similar-grained data can be accommodated.

When facts are derived from disparate sources, a monolithic design is not practical. In this case, multiple fact tables can be conformed by …