Tableau works great with a long list of data sources; both traditional databases, OLAP databases, file-based data sources like CSV and Excel, cloud data sources like Google Analytics, Google BigQuery, Amazon Redshift, SalesForce.com and a wide variety of Hadoop-like databases.
Most parts of Tableau works the same on all the different data sources. You get the same intuitive user interface there makes it easy for end users to create great looking dashboards and analyses. You have map powerful functionality out-of-the-box. There are too many great things about Tableau to list them all – so look at their website for more info on functionality and the great look-and-feel: www.tableausoftware.com
However, there are some differences between the different data sources. Especially when working with cubes we see some end user frustration because they don’t have the same flexibility as when working the relational data or extracts.
That is the reason for this series – to explore Tableau in the context of an Analysis Services cube.
But first all the important documentation from Tableau on working with cubes. There are not that much info and a lot is learning by doing.
The next post in this series will be on cube design for Tableau.