Don’t move your data – virtualize it!

Don’t Move Your Data – virtualize it!

By Paul Dimarzio, IBM


I am a huge proponent of analyzing data in-place, at its point of origin. There are SO many benefits!!! You get better results because you’re working off the freshest data, and you get lower costs because you’re not burning cycles copying data to server farms (also an unnecessary cost).

One of the key enablers of in-place analytics is data virtualization, essentially mirroring your active data stores in-memory where they can be processed with speed and at extremely low cost. And one of the best technologies that I know of for this is Rocket Data Virtualization, from Rocket Software. It’s the technology that allows us to deliver first-class support for Spark and IBM Machine Learning on the mainframe.

Rocket’s Bryan Smith, VP, R&D & Chief Technology Officer, writes and speaks about data virtualization quite a bit – as in this recent report. I encourage you to follow him ( and seriously consider data virtualization before you start your next ETL project.

The first time I met Bryan was at a conference in 2014, where he was handing out these awesome anti-ETL buttons (I still have mine, Bryan!).

If you don’t believe that ETL is a huge and unnecessary drain on your resources, I recommend you check out this paper from Clabby Analytics. I guarantee that it will give you some things to think about!

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