As evidenced in the previous sections, there are a plethora of options available for data governance; choosing the right tool depends primarily on the use case and the level of governance you are attempting to implement. We also see that the market is flooded with umpteen numbers of tools that make decision making very difficult. The following figure depicts the key aspects that are to be considered while choosing the right tools and technologies for Data Governance:
Data Lake Development with Big Data
Data Lake Development with Big Data
Overview of this book
A Data Lake is a highly scalable platform for storing huge volumes of multistructured data from disparate sources with centralized data management services. This book explores the potential of Data Lakes and explores architectural approaches to building data lakes that ingest, index, manage, and analyze massive amounts of data using batch and real-time processing frameworks. It guides you on how to go about building a Data Lake that is managed by Hadoop and accessed as required by other Big Data applications.
This book will guide readers (using best practices) in developing Data Lake's capabilities. It will focus on architect data governance, security, data quality, data lineage tracking, metadata management, and semantic data tagging. By the end of this book, you will have a good understanding of building a Data Lake for Big Data.
Table of Contents (13 chapters)
Data Lake Development with Big Data
Credits
About the Authors
Acknowledgement
About the Reviewer
www.PacktPub.com
Preface
Free Chapter
The Need for Data Lake
Data Integration, Quality, and Enrichment
Data Discovery and Consumption
Data Governance
Index
Customer Reviews