Data Management at Scale: Modern Data Architecture with Data Mesh and Data Fabric, Second Edition (Final Release)

Data management is an emerging and disruptive subject. Datafication is everywhere. This transformation is happening all around us: in smartphones, TV devices, ereaders, industrial machines, self-driving cars, robots, and so on. It’s changing our lives at an accelerating speed. As data management continues to evolve rapidly, managing all of your data in a central place, such as a data warehouse, is no longer scalable. Today's world is about quickly turning data into value. This requires a paradigm shift in the way we federate responsibilities, manage data, and make it available to others. With this practical book, you'll learn how to design a next-gen data architecture that takes into account the scale you need for your organization. Executives, architects and engineers, analytics teams, and compliance and governance staff will learn how to build a next-gen data landscape. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. In the Chapter 1 I’ll discuss each of these and its influence on data management. Firstly, analytics is fragmenting the data landscape because of use case diversity; Secondly, new software development methodologies make data harder to manage; Thirdly, cloud computing and faster networks fragment data landscapes; Fourthly, there are privacy, security, and regulatory concerns; Fifthly, the rapid growth of data and intensive data consumption make operational systems suffer; Lastly, data monetization requires an ecosystem-to-ecosystem architecture. The impact these trends have on data management are tremendous and force the whole industry to rethink how data management must be conducted in the future. Examine data management trends, including regulatory requirements, privacy concerns, and new developments such as data mesh and data fabric Go deep into building a modern data architecture, including cloud data landing zones, domain-driven design, data product design, and more Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata Who Is This Book For? This book is intended for large enterprises, though smaller organizations may find much of value in it. It’s geared toward: Executives and architects Chief data officers, chief technology officers, chief architects, enterprise architects, and lead data architects Analytics teams Data scientists, data engineers, data analysts, and heads of analytics Development teams Data engineers, data scientists, business intelligence engineers, data modelers and designers, and other data professionals Compliance and governance teams Chief information security officers, data protection officers, information security analysts, regulatory compliance heads, data stewards, and business analysts