Unleashing Data Governance and Data Mesh in the age of Generative AI: A comprehensive guide for AWS cloud by Harsha Tadiparthi, Joel Farvault, Navneet Srivastava
English | November 13, 2024 | ISBN: N/A | ASIN: B0DN27GXP4 | 382 pages | EPUB | 16 Mb
Master the art of modern data governance and data mesh with AWS in this age of AI, empowering you to confidently lead your organization's data initiatives and unlock unprecedented value from your data assets.
Book Description
In our conversations with IT leaders and professionals across diverse industries and organizations of varying sizes, one consistent theme emerged: the challenge of proper data governance is a persistent source of anxiety. These leaders have candidly shared their struggles, painting a vivid picture of the complexities they face. At the forefront are issues such as managing fragmented data landscapes, unclear delineation of roles and responsibilities, the delicate balance between data accessibility and security, and the ongoing need to adapt governance strategies as data volumes surge and regulatory landscapes shift. A striking consensus among these leaders reveals a sobering self-assessment of their organizations' data governance capabilities, often described as inadequate. Most express a keen interest in implementing a data mesh architecture yet find themselves at a loss when it comes to envisioning and executing effective data mesh in their data governance framework, particularly in the era of generative AI.
This comprehensive book offers an end-to-end exploration of data governance, data mesh architecture, and their integration with generative AI, focusing on real-world use cases within AWS environments. It addresses the challenges faced by IT leaders and IT professionals outlined above. It tackles the democratization of data and AI, covering crucial topics such as data quality, privacy, ethics, and model transparency. The book delves into the principles of data mesh, modern data strategies, and fundamental aspects of data governance, providing practical insights into AWS services that support these implementations.
By the end of this book, you will be equipped with a thorough understanding of the practical implementation patterns required to construct a robust data governance framework using data mesh principles, all leveraging the power of AWS services. This book serves as your roadmap to mastering the essential elements of modern data management, ensuring you're well-prepared to lead your organization's data initiatives with confidence and expertise.
Who this book is for?
Whether you're a strategic decision-maker or a technical implementer, this book equips you with the necessary tools and understanding to navigate the complex landscape of modern data governance and analytics. It serves as an indispensable resource for data leaders and architects who will find invaluable insights to establish a robust data governance framework for their organizations, both structured and unstructured data. Hands-on practitioners such as data engineers, data stewards, and data admins will benefit from practical implementation guidance to build, consume, and administer data products using the AWS cloud. The book also caters to ML practitioners, offering effective guidance on model governance and self-service ML development that is particularly relevant in the emerging era of generative AI.
Table Of Contents
Chapter 1, Decoding Data Mesh and Data Governance in the Era of Generative AI
Chapter 2, Data Management and Support for Generative AI
Chapter 3, Data Governance in action using AWS Services
Chapter 4, Democratizing Generative AI: Governing the unstructured data frontier
Chapter 5, Data Mesh on AWS
Chapter 6, Approach to building a Data Mesh on AWS
Chapter 7, Services to power your data mesh
Chapter 8, Build a Data Product on a Big Data Platform
Chapter 9, Build a Data Product on a Data Warehouse
Chapter 10, Self-service Data Mesh: Democratize Analytics and AI using Amazon DataZone
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