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Volume 30, Issue 1

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Wednesday, 15 May 2013 15:45

Securing Hadoop Data: 10 Best Practices

Storing data in Hadoop has become a common practice in IT these days. However, there are some concerns about securing sensitive data in Hadoop. Dataguise, a maker of data security intelligence and protection solutions, has provided us with 10 security best practices for organizations considering or implementing Hadoop. By following these procedures to provide privacy risk, data and security management, enterprises can prevent costly exposure of sensitive data, reduce their risk profile and better adhere to compliance mandates. These practices and procedures come from Dataguise's experience in securing large and diverse environments. The explosion in information technology tools and capabilities has enabled advanced analytics using big data. However, the benefits of this new technology area are often coupled with data privacy issues. In these large information repositories, personally identifiable information (PII) such as names, addresses and social security numbers may exist. Financial data such as credit card and account numbers might also be found in large volumes across these environments and pose serious concerns related to access. Through careful planning, testing, pre-production preparation and the appropriate use of technology, much of these concerns can be alleviated.