In today’s data driven world, analyzing data is key to 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 Teradata, Oracle, and Microsoft SQL Server have had this ability for many years and we are now starting to see some of this in the world of Big Data with products like Apache Kylin, Arcadia Data, and Cloudera Impala.

While Hadoop and the NoSQL technologies continue to evolve and as more and more data is stored in things like HDFS, it is good to see companies like Teradata continue to invest in multidimensional data analytics.  Teradata recently announced version 15.10 of Teradata OLAP.  Mark Hasenstab at Teradata posted a blog talking about some of the new capabilities of Teradata OLAP.  What is really powerful about Teradata OLAP is that you can define a schema on top of your data in Teradata 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 Teradata 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 Teradata has the ability to pull Hadoop data in, you could in theory do multidimensional analytics on your data in Hadoop – basically use Teradata to front your Hadoop 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 Teradata and Hadoop, this becomes a good solution.