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5 Security Requirements For Big Data Hadoop Implementations

Identifying and securing sensitive data in Apache Hadoop deployments is a challenge, according to security firm Dataguise.

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Hadoop Prompts Data Control, Security Challenges

Using advanced analytics such as Hadoop to mine big data implementations in the enterprise has raised concerns about how to secure and control the data repositories. By distributing data storage and data management across a large number of nodes, you can attack a large problem with parallelism and get results from large bodies of data a lot faster. With Hadoop, there is less dependence on a strict data schema so a greater volume of data can be ingested giving analysts more flexibility and speed. However, the approach can cause challenges in identifying and securing sensitive data, according to Fremont, Calif.-based Dataguise, which sells a data governance and encryption platform.

 
 
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