This chapter explained in detail Data Governance and the ways to manage data with focus on its availability, usability, integrity, retention, and security. We started with understanding data governance and why it is needed and then understood how data governance on the Data Lake is far more efficient when compared to traditional governance. We also took a look at a few practical scenarios to comprehend the real-life use cases of Data Governance.

We took a deep dive into Data Governance and its components, such as data security and privacy, metadata management and lineage tracking, Information Lifecycle Management, and how they cut across all the three tiers of Data Lake, such as Data Intake, management, and consumption. In the subsequent sections, we took a look at the various Big Data tools and technologies that can be used to perform data governance to help you in decision making and to arrive at the set of technologies that can be used for specific use cases by giving an overview...