Why Have A Date Dimension

Thomas LeBlanc discusses reasons for having a date dimension in a data warehouse:

The date dimension can also contain columns for Weekend versus Weekday, Holiday and month markers like 2014-10 or by quarter like 2014-Q1. All these can be computed once in the dimension table and used at will by query writers. They now do not have to know how to use T-SQL functions or concatenate substrings of “CASTed” date columns.

Then, when the DimDate is related to various Fact tables and processed into an OLAP cube, the measures and aggregations are displayable side by side through the DimDate dimension which is now considered a Conformed Dimension. The slicing and dicing of data has just been made a whole lot easier.

I’d go a step further and say that every instance should have access to a tally table and a date table.

Related Posts

Gartner’s BI Magic Quadrant For 2018

Bruno Aziza looks at the new Gartner magic quadrant for business intelligence solutions: For the first time in 3 years, Gartner dropped a significant amount of vendors off its quadrant.  There were 24 vendors in the firm’s quadrant in 2016 and 2017.  This year, the Magic Quadrant only lists 20 vendors…that’s a 16% quadrant reduction.  Has […]

Read More

The Importance Of A Data Computing Layer For Reporting

Buxing Jiang argues that there are reporting scenarios in which building a data computing layer is critical: In previous articles, we mentioned that most reporting performance issues need to be addressed during the data preparation stage, but many scenarios can’t be handled within the data source. For example, parallel data retrieval should be performed outside of […]

Read More


June 2016
« May Jul »