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Data Vault and Data Virtualization: Double Agility


September 10, 2014 - 0 Comments

Rick van der Lans is data virtualization’s leading independent analyst.  So when he writes a new white paper, any enterprise that is struggling to connect all their data (which is pretty much every enterprise), would be wise to check it out.

Rick’s latest is Data Vault and Data Virtualization: Double Agility. In a nutshell, the paper addresses how enterprises can craftily combine the Data Vault approach to modeling enterprise data warehouses with the data virtualization approach for connecting and delivering data.  The result is what Rick calls double agility as each approach accelerates time to solution in complex data environments.

Data Vault Pros and Cons

Adding new data sources such as big data and cloud to an existing data warehouses is difficult. The Data Vault approach provides the extensibility required.  This is the first agility.

Unfortunately, from a query and reporting point of view developing reports straight for a Data Vault‐based data warehouse results in complex SQL statements that almost always lead to bad reporting performance. The reason is Data Vault models distribute data over a large number of tables.

Losing Agility Due to Data Mart Proliferation

To solve the performance problems with Data Vault, many enterprises have built physical data marts that reorganize the data for faster queries.

Unfortunately valuable time must be spent on designing, optimizing, loading, and managing all these data marts.   And any new extensions to the enterprise data warehouse must be re-implemented across the impacted marts.

Data Virtualization Returns the Agility

To avoid the data mart workload, yet retain agile warehouse extensibility, Rick has worked with Netherlands based system integrator Centennium and Cisco to provide a better, double agility, alternative.

In this new solution, Cisco Data Virtualization, together with a Centennium-defined data modeling technique called SuperNova, replaces all the physical data marts.  So, no valuable time has to be spent on designing, optimizing, loading, managing and updating these derived data marts. Data warehouse extensibility is retained, but because the reporting is based on virtual, rather than physical models, they are very easy to create and maintain.

Meet Rick van der Lans at Data Virtualization Day

To learn more about this innovative solution as well as data virtualization in general, come to Data Virtualization Day 2014 in New York City on October 1.  Rick, along with the also sharp Barry Devlin, will join me on stage for the Analyst Roundtable. I hope to see you there.

 

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To learn more about Cisco Data Virtualization, check out our page

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