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How big data tools and technologies can be protected from risk

Enterprises are increasingly turning their focus to big data tools and technologies, both in their role as an instrument for driving security and as an asset that requires protection. This video explains big data's place in emerging security architectures, and the controls and mitigations enterprises can implement in their big data environments and the surrounding systems to improve security overall.

Enterprises using big data tools and technologies build data lakes, which aggregate and store tons of information from a variety of systems important to business operations. No matter if it's data on users, employees' physical locations or enterprise intellectual property, this information needs to be secured against attackers. "If it's valuable to you, it's likely to be valuable to someone else as well," warns John Burke, CIO and principal research analyst at Nemertes Research who has vast experience in technology, including end-user support, programming, system administration and network architecture.

Burke explains how to protect big data tools and technologies using the available controls in the tools themselves, which users may not realize must be configured or turned on. Examples of such features include authentication of users and services, access controls, and encryption of data at rest and in motion. The environment where the big data platform exists will also have standard security measures that can be enforced.

Burke introduces several key vendors offering security tools with specific features that can be layered on, such as auditing for specific compliance regulations, data masking and tokenization, as well as backup. He wraps up with some recommendations for assessing the different types of risks surrounding the use of big data tools and technologies at each step of implementation and how this information can be folded into an enterprise's business risk portfolio.

Watch this video to learn more about what your enterprise should consider when using big data tools and technologies.

 

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