Multidimensional Data Analytics with MS SQL Server OLAP

Multidimensional data analytics with MS SQL Server OLAP

In today’s data driven world, analyzing data is key tmultidimensional-dao success. Analyzing data across multiple dimensions has always been an important concept and one of the major tools to do this has always been Microsoft Excel Pivot Tables. To support multidimensional data analytics with pivot tables requires the ability to model and aggregate data. Traditional data sources like SAP, Oracle, and Microsoft SQL Server have had this ability for many years and we are now starting to see some of this in Microsoft BI Tools.

What is really powerful about MS BI Tools is that you can define a schema on top of your data and then quickly slice and dice your data in products like Excel Pivot Tables or Tableau. There is no need to move your data or re-structure your data. The other advantage of Microsoft BI OLAP is that this is an established product so supports a wide variety of BI tools including Microsoft Excel, Tableau, SAP Business Objects, and Datawatch.

What is also more interesting about this solution is that since Microsoft has the ability to pull Hadoop data in, you could in theory do multidimensional analytics on your data in Hadoop – basically use MS BI to front your data and then have OLAP and pivot table type analytics on your Hadoop data. Granted this is a heavier solution than doing OLAP directly on the Hadoop data but if you live in a heterogeneous world of MS BI and Hadoop, this becomes a good solution.