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Mastering Hadoop 3

You're reading from  Mastering Hadoop 3

Product type Book
Published in Feb 2019
Publisher Packt
ISBN-13 9781788620444
Pages 544 pages
Edition 1st Edition
Languages
Authors (2):
Chanchal Singh Chanchal Singh
Profile icon Chanchal Singh
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details
Toc

Table of Contents (23) Chapters close

Title Page
Dedication
About Packt
Foreword
Contributors
Preface
1. Journey to Hadoop 3 2. Deep Dive into the Hadoop Distributed File System 3. YARN Resource Management in Hadoop 4. Internals of MapReduce 5. SQL on Hadoop 6. Real-Time Processing Engines 7. Widely Used Hadoop Ecosystem Components 8. Designing Applications in Hadoop 9. Real-Time Stream Processing in Hadoop 10. Machine Learning in Hadoop 11. Hadoop in the Cloud 12. Hadoop Cluster Profiling 13. Who Can Do What in Hadoop 14. Network and Data Security 15. Monitoring Hadoop 1. Other Books You May Enjoy Index

Data governance


Data governance is the process of ensuring  high quality, high availability, usability, integrity, and security of the data that's used across the organization. Data governance helps the organization to efficiently manage the data it has and get more value from that data, along with making the important value of that data visible to users. 

Data governance enables and encourages good behavior about data and also limits any behavior that create risks. This objective is similar, irrespective of whether we are in a big data environment or a traditional data management environment. It helps the organization identify who is responsible for the data, collaborate to set policies and decisions, analyse how the data is used and what it is for, understand how and where metrics and information are derived, and determines the impact of any change in data on the business.

Data governance pillars

There are multiple definitions you will find about data governance pillars; we have defined three...

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