Data Fabric and Data Mesh Approaches with AI: A Guide to AI-based Data Cataloging, Governance, Integration, Orchestration, and Consumption
- Length: 458 pages
- Edition: 1
- Language: English
- Publisher: Apress
- Publication Date: 2023-04-28
- ISBN-10: 1484292529
- ISBN-13: 9781484292525
- Sales Rank: #1468198 (See Top 100 Books)
Understand modern data fabric and data mesh concepts using AI-based self-service data discovery and delivery capabilities, a range of intelligent data integration styles, and automated unified data governance―all designed to deliver “data as a product” within hybrid cloud landscapes.
This book teaches you how to successfully deploy state-of-the-art data mesh solutions and gain a comprehensive overview on how a data fabric architecture uses artificial intelligence (AI) and machine learning (ML) for automated metadata management and self-service data discovery and consumption. You will learn how data fabric and data mesh relate to other concepts such as data DataOps, MLOps, AIDevOps, and more. Many examples are included to demonstrate how to modernize the consumption of data to enable a shopping-for-data (data as a product) experience.
By the end of this book, you will understand the data fabric concept and architecture as it relates to themes such as automated unified data governance and compliance, enterprise information architecture, AI and hybrid cloud landscapes, and intelligent cataloging and metadata management.
What You Will Learn
- Discover best practices and methods to successfully implement a data fabric architecture and data mesh solution
- Understand key data fabric capabilities, e.g., self-service data discovery, intelligent data integration techniques, intelligent cataloging and metadata management, and trustworthy AI
- Recognize the importance of data fabric to accelerate digital transformation and democratize data access
- Dive into important data fabric topics, addressing current data fabric challenges
- Conceive data fabric and data mesh concepts holistically within an enterprise context
- Become acquainted with the business benefits of data fabric and data mesh
Who This Book Is For
Anyone who is interested in deploying modern data fabric architectures and data mesh solutions within an enterprise, including IT and business leaders, data governance and data office professionals, data stewards and engineers, data scientists, and information and data architects. Readers should have a basic understanding of enterprise information architecture.
Cover
Front Matter
Part I. Data Fabric and Data Mesh Foundation
1. Evolution of Data Architecture
2. Terminology: Data Fabric and Data Mesh
3. Data Fabric and Data Mesh Use Case Scenarios
4. Data Fabric and Data Mesh Business Benefits
Part II. Key Data Fabric and Data Mesh Capabilities and Concepts
5. Key Data Fabric and Data Mesh Capabilities
6. Relevant ML and DL Concepts
7. AI and ML for a Data Fabric and Data Mesh
8. AI for Entity Resolution
9. Data Fabric and Data Mesh for the AI Lifecycle
Part III. Deploying Data Fabric and Data Mesh in Context
10. Data Fabric Architecture Patterns
11. Data Fabric Within an Enterprise Architecture
12. Data Fabric and Data Mesh in a Hybrid Cloud Landscape
13. Intelligent Cataloging and Metadata Management
14. Automated Data Fabric and Data Mesh Aspects
15. Data Governance in the Context of Data Fabric and Data Mesh
Part IV. Current Offerings and Future Aspects
16. Sample Vendor Offerings
17. Data Fabric and Data Mesh Research Areas
18. In Summary and Onward
Back MatterDonate to keep this site alive
How to download source code?
1. Go to: https://github.com/Apress
2. In the Find a repository… box, search the book title: Data Fabric and Data Mesh Approaches with AI: A Guide to AI-based Data Cataloging, Governance, Integration, Orchestration, and Consumption, sometime you may not get the results, please search the main title.
3. Click the book title in the search results.
3. Click Code to download.
1. Disable the AdBlock plugin. Otherwise, you may not get any links.
2. Solve the CAPTCHA.
3. Click download link.
4. Lead to download server to download.
