#1 Think about security before you start your big data project:

It is not recommended to wait till a data breach. Organizations need to find ways in securing their precious data before anyone can get hold of it. This also puts IT security team and others in perspective as they need to have serious panel discussion on data security and issues related during installation and supply into the Hadoop cluster.

#2 Consider what data may get stored:

Data’s mustered into Hadoop for storing and for running analytics must be subjected to regulation and specific security measures. Although it is hard to imply security on data transfer and usage, enterprises need to think of the revenue loss and risk associated with a data breach or leakage.

#3 Centralize accountability:

At present, the data availability across enterprises is so vivid that they aren’t well organized and well arranged. This creates diversity across the organization in terms of data positioning. Centralizing the accountability for data security is a good method for better policy enforcement and improved control over the data set.

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