Big Data security mistakes, tips and tricks
by Mirko Zorz - Wednesday, 9 July 2014.
In general terms, what’s needed is an approach to Big Data management that secures the data from top-to-bottom; an approach that is designed specifically to protect the data that it is managing. The solution should “own” the data in the sense that it is fully responsible for governing access to the data and does not delegate parts of that task to other services that may not have been designed for the task. At the same time, the chosen data management solution must integrate with the rest of the established security infrastructure within the enterprise. In the case of user account management and authentication, for example, then the solution must be able to integrate with LDAP and Active Directory services.

What are some of the most obvious mistakes that companies make with their Big Data projects?

Many companies make the mistake of trying to build a secure big data solution themselves from open source software projects. For example, it is tempting to take projects from the Hadoop ecosystem and integrate them together to provide a data management system. After all, the software is free, right? The harsh truth is that such approaches are free if your time isn’t valuable. There are so many moving parts to a Hadoop system that it makes securing data from end-to-end extremely difficult.

In the long run, the most cost effective way of securing Big Data is to select a data management solution that is designed from the ground up to protect data at scale. It takes a long time to develop a robust, secure data management system, and it is far better to choose a proven solution that is tailored to meet the security and compliance requirements of your business, on your storage platform of choice, rather than attempting to build one yourself.

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