Jason Hare

“The Scaled Architecture you will discover in this book comes with a large set of data management principles. It requires you, for example, to identify and classify genuine and unique data, fix data quality at the source, administer metadata precisely, and draw boundaries carefully. When enterprises follow these principles, they empower their teams to distribute and use data quickly while staying decoupled. This architecture also comes with a governance model: engineers need to learn how to make good abstractions and data pipelines, while business data owners need to take accountability for their data and its quality, ensuring that the context is clear to everyone.”
― Piethein Strengholt, Data Management at Scale: Best Practices for Enterprise Architecture

“What I envision is an architecture that brings all the data management areas much closer together by providing a consistent view of how to uniformly apply security, governance, master data management, metadata, and data modeling, an architecture that can work using a combination of multiple cloud providers and on-premises platforms but still gives you the control and agility you need. It abstracts complexity for teams by providing domain-agnostic and reusable building blocks but still provides flexibility by providing a combination of different data delivery styles using a mix of technologies.”
― Piethein Strengholt, Data Management at Scale: Best Practices for Enterprise Architecture