Sharing Big Data Safely (O'Reilly)
Wednesday, 16 March 2016

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 practical book subtitled "Managing Data Security", Ted Dunning and Ellen Friedman offer two novel and practical solutions that you can implement right away. 

<ASIN:1491952121>

Ideal for both technical and non-technical decision makers, group leaders, developers, and data scientists, this slim book 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 open source SQL query engine 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.

 

Authors: Ted Dunning and Ellen Friedman
Publisher: O'Reilly
Date: January 8, 2016
Pages: 96
ISBN: 978-1491952122
Print: 1491952121
Kindle: B019D5KU3E

 

 

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Publisher: Manning
Date: January 2020
Pages: 248
ISBN: 978-1617296086
Print: 1617296082
Audience: Python developers
Rating: 3
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Query Store for SQL Server 2019 (Apress)

Author: Tracy Boggiano & Grant Fritchey
Publisher: Apress
Pages: 234
ISBN: 978-1484250037
Print: 1484250036
Kindle: B07YNL3X4X
Audience: SQL Server DBAs and Devs
Rating: 4
Reviewer: Ian Stirk

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