The proverbial cobbler feverishly churns out shoes for his customers while his own children roam the streets with bare feet. Similarly, IT departments throughout the world are exerting enormous effort implementing big data projects for their line of business (LOB) partners, all the while a killer use case for the technology is hiding right under their noses.

IT infrastructures generate massive amounts of data. For example, tracking the storage access pattern of a virtual machine would require hundreds of megabytes per day. Hence, adding this level of visibility to a typical virtualized data center will produce terabytes of data each week. Sorting through this mound of information in a timely manner to draw relevant conclusions would require an analytics engine that can churn through hundreds of terabytes of data with ease and novel algorithms to make sense of it all – the very definition of big data! 

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