All Indian Reprints of O'Reilly are printed in Grayscale._x000D_ Many big data-driven companies today are moving to protect certain types of data against intrusion, leaksor unauthorized eyes. But how do you lock down data while granting access to people who need to see it? In this practical book, authors Ted Dunning and Ellen Friedman offer two novel and practical solutions that you can implement right away._x000D_ _x000D_ Ideal for both technical and non-technical decision makers, group leaders, developersand data scientists, this book shows you how to:_x000D_ _x000D_ Share original data in a controlled way so that different groups within your organization only see part of the whole._x000D_ You’ll learn how to do this with the new open source SQL query engine Apache Drill._x000D_ 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._x000D_ If you’re intrigued by the synthetic data solution, explore the log-synth program that Ted Dunning developed as open source code (available on GitHub), along with how-to instructions and tips for best practice. You’ll also get a collection of use cases._x000D_ Providing lock-down security while safely sharing data is a significant challenge for a growing number of organizations. With this book, you’ll discover new options to share data safely without sacrificing security.