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Data Digest: Data Lakes versus Streams, Legal and Security Problems for Big Data

Read about the relative benefits of data lakes and data streams, how to avoid discriminatory results in big data analytics, and how to improve security for your big data environment.

Use Both Data Lakes and Streams for Best Results

Data professionals disagree about the relative value of data lakes and data streams. However, this article contends that each has its own niche: data streams for real-time data analysis and data lakes for access to a large variety of stored data.

Read more at Information Age

Avoid Accidental Big Data Discrimination

As the number of data sources and variables grows, so does the potential for unintended consequences from big data analytics. If a variable in your algorithm correlates with a protected characteristic (such as race, age, or gender), your results could be discriminatory, and you could be legally liable. This article discusses how to avoid disparate impact when using big data.

Read more at MarketWatch

Counteract Big Data Security Headaches

More enterprises are storing sensitive information in big data environments, but big data systems are hard to secure. This article reviews the major challenges in protecting big data and recommends best practices for security.

Read more at VPN Haus

About the Author

Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.


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