The Wikipedia definition of Big Data is "a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis and visualisation."
This focus on analysis and processing is far from rare. Indeed, any Big Data oriented conversation will almost inevitably be built around the data science for want of a better word. Unfortunately, with Big Data moving out of the realm of hyperbole (Time magazine had Big Data as the second biggest buzzword of 2012, just behind Fiscal Cliff) and firmly into the reality of the enterprise, a better word that is all too often missing from the conversation is 'security'.
It's not just the new-found availability of that data and the fact that the tools are still very immature, but also the potential sensitivity of the information hidden inside that data that can now be discovered, that brings security challenges.
Is Big Data deployment within the enterprise really in danger of sleepwalking into trouble just as early cloud adoption strategies stumbled when it came to a largely ROI-driven adoption without much (or indeed any) pre-deployment strategic thinking about the security issues?
Alex Raistrick, director for Western Europe at Palo Alto Networks, certainly agrees that there has been a rush to store all this data without too much thought about how it will be processed and controlled in the future.
"All data that is stored has a purpose and a security risk associated with that purpose. If the data stores are allowed to grow at their current rate (reported to be 2.5 quintillion bytes of data a day world-wide) businesses will have no idea where their risk lies and how to mitigate it," Raistrick says.
