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Sharing Big Data Safely

Many big data-driven companies today are moving to protect certain types of data against intrusion, leaks, or unauthorized eyes. But how do you lock down data while granting access to people who need to see it? In this O’Reilly report, authors Ted Dunning and Ellen Friedman offer two novel and practical solutions that you can implement right away. Ideal for both technical and non-technical decision makers, group leaders, developers, and data scientists, this report shows you how to:

  • Share original data in a controlled way so that different groups within your organization only see part of the whole. You’ll learn how to do this with the new SQL-on-Hadoop open source tool, Apache Drill.
  • Provide synthetic data that emulates the behavior of sensitive data. This approach enables external advisors to work with you on projects involving data that you can't show them.

Providing lock-down security while safely sharing data is a significant challenge for a growing number of organizations. Read this report to discover new options to share data safely without sacrificing security.


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