Large organizations worldwide are working to develop and deploy Big Data analytical facilities alongside their established business intelligence infrastructure. These initiatives are motivated in nearly equal parts by the conviction that new business insights and opportunities are buried in the avalanche of new data, by the knowledge that conventional business intelligence systems are unequal to the task, and by the fear that competitors will be first to master and exploit the available new data streams.

Because the phenomenon of Big Data analytics is only a few years old, few standards exist to ensure that these new systems and the analytical activities they support are successfully integrated into the existing policy frameworks that ensure governance, compliance and security. One of those critical policy domains—data security—has the potential to arrest many of these developments and block the realization of their business benefits if not adequately addressed. This paper presents a comprehensive solution that cost-effectively ensures the security of sensitive information in Big Data environments without impairing their operational flexibility or computational performance.

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