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Data Protection: Classifying and Protecting Big Data

ScottBaker ‎11-13-2013 05:00 AM - edited ‎02-19-2015 12:50 PM

These days, “virtualization” has become synonymous with “Big Data.” Regardless of how you classify the kind of data that comprises Big Data, it is all boils down to distilling information from all the 1s and 0s in order to make some type of informed decision – ideally that decision results in revenue or cost savings. 


Regardless of the data’s use or size, how it is protected is as important as how it is analyzed. “Protection” can mean different things depending on who you ask, but there is one simple truth in IT – placing it on the right infrastructure tier determines the speed at which that data can be recovered.  Choosing the right tier is based upon your commitment to properly categorizing the data juxtaposed to its referential value, or probability of reuse, to the business. 


At VMWorld 2013 in Barcelona, I had an opportunity to expand on this with W. Curtis Preston of TruthInIT.  In the interview, Curtis and I explored the aspects of Big Data, and how an IT administrator can use the referential value of data to determine the right infrastructure tier and best protection configuration using three data classifications tied to its business criticality. The onus of data classification is on the IT staff. Once properly classified, picking the right tier becomes easier – as does meeting the service level agreements you’ve committed to. I enjoyed bantering with Curtis and I hope you find the discussion informative. I’d love to hear your thoughts on our dialogue.


Watch the video podcast on TruthInIT’s site.


You can read more about VMWorld 2013 on my colleague, Stephen Spellicy’s post




About the Author


Scott speaks, blogs, writes articles and specializes in driving competitively differentiated integrations for storage and virtualization. VMware Certified Professional, recognized as a vExpert, VMWorld speaker, VMUG keynote speaker, and a contributing author of the book Virtualization Changes Everything.

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