Ten Mistakes to Avoid In Dimensional Modeling

Ten Mistakes to Avoid In Dimensional Modeling

December 5, 2011

By Christopher Adamson

A dimensional model transforms data into information—the fundamental objective of every business intelligence (BI) program. Although it has become the de facto standard for data mart design, common mistakes disrupt this crucial function.

The dimensional model is more capable than is generally understood. Often pigeonholed as a data model, it is not exploited as a presentation model in a federated environment, or as a requirements model. Entire subject areas are closed off by the common misconception that some things can only be modeled using entity-relationship techniques.

To attain the full potential of your dimensional model, it is necessary to master a broad range of principles, understand how and what to model, and avoid lapsing into habits from other modeling disciplines.

A dimensional model of your business is an important asset of your BI program. Maximize its value by avoiding these 10 mistakes.