Summary

Data Governance must be designed end to end across all the phases (Create, Ingest, Integrate, Consume, Archive, and Destroy) in a data life cycle. In this chapter, we defined a Data Governance architecture as being metadata-driven and event-driven We also defined what it means to manage metadata as a service, which focuses on the collection, integration, and storage of distributed metadata to derive insights and take action. We learned that a Data Governance layer consists of two components: active metadata and life cycle governance. We also understand that the brain of the Data Fabric architecture is active metadata, which is represented by a Metadata Knowledge Graph. The life cycle governance component consists of capabilities that are centered around Data Governance pillars such as Data Privacy, Protection, and Security, Data Quality, Data Lineage, MDM, and Metadata Management.

In the next chapter, we will focus on the two other layers in a Data Fabric architecture:...