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Data Management at Scale - 2nd Edition by Piethein Strengholt (Paperback)
About this item
Highlights
- 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.
- Author(s): Piethein Strengholt
- 409 Pages
- Computers + Internet, Data Modeling & Design
Description
About the Book
"Data management is subject to disruption. Trends like artificial intelligence, cloudification, ecosystem connectivity, microservices, open data, software as a service, and new software delivery models are causing a paradigm shift in the way data management is practiced. Organizations need to face the fact that decentralization is inevitable. In this practical book, author Piethein Strengholt explains how to establish a future-proof and scalable data management practice. He'll cut through new concepts like data mesh and data fabric and demonstrate what a next-gen data architecture will look like. Executives, architects and engineers, analytics teams, and compliance and governance staff will learn how to shape data management according to their needs. Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed."--Book Synopsis
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.
- 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