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Data Fabric: An Intelligent Data Architecture for AI [Minkštas viršelis]

  • Formatas: Paperback / softback, 104 pages, aukštis x plotis: 229x152 mm
  • Išleidimo metai: 01-Dec-2022
  • Leidėjas: MC Press, LLC
  • ISBN-10: 158347904X
  • ISBN-13: 9781583479049
Kitos knygos pagal šią temą:
  • Formatas: Paperback / softback, 104 pages, aukštis x plotis: 229x152 mm
  • Išleidimo metai: 01-Dec-2022
  • Leidėjas: MC Press, LLC
  • ISBN-10: 158347904X
  • ISBN-13: 9781583479049
Kitos knygos pagal šią temą:
Many organizations recognize the value and benefits Artificial Intelligence (AI) can bring if implemented correctly. This topic is outlined in the authors’ previous book, Artificial Intelligence: Evolution and Revolution. A long-standing challenge that many organizations continue to face is preparing for AI and making sure that their data and assets are accessible, manageable, and governed and are of the right quality so that they can be consumed by new and existing AI applications in order to infuse AI across the enterprise to help drive smarter business outcomes. Over the years, numerous paradigms and efforts have attempted to address the complexities of managing sprawling and disparate data silos, but all seemed to have fallen short of their promises and expectations. Organizations need the flexibility to put their data and assets where it makes most business sense, whether that’s on premises or in the private or public cloud. This book attempts to explain the concepts and values that a data fabric approach can deliver to both technical and business communities.
Acknowledgments iii
Foreword vii
1 In the Beginning
1(6)
Early Data Storage and Management
1(3)
From Centralized to Distributed
4(1)
Databases, OLTP, OLAP, Warehouses, Master Data Management, Marts, Lakes, Lakehouses, Hadoop
5(2)
2 The Impact of Hybrid Cloud
7(10)
The Goal of Cloud
7(3)
The Roles of Different "As a Service" Models
10(4)
Red Hat Open Shift Container Platform
14(3)
3 The Journey to AI
17(4)
The Best Performers Are Data-Driven
17(4)
4 Reducing Complexity with a Data Fabric
21(10)
Data Fabric vs. Data Mesh
24(1)
Delivering a Data Fabric as Part of a Hybrid Cloud Data and AI Platform
25(2)
Automation: The Key to Agility
27(2)
Data and AI: How and Where the Users Need It
29(2)
5 The Data Fabric Advantage
31(8)
Data Fabric vs. Data Virtualization
33(3)
Other Advantages of Data Fabric Architectures
36(3)
6 Data Fabric, DataOps, and the Data Catalog
39(8)
Data Catalog Attributes and Benefits
40(3)
Using a Data Catalog to Improve Business Taxonomy
43(4)
7 Common Use Cases for a Data Fabric
47(24)
Use Case 1 Driving Simpler Cloud Integration
47(5)
Use Case 2 Going 360 Degrees
52(3)
Use Case 3 True Enterprise Governance
55(5)
Use Case 4 Toward Trustworthy, Transparent AI
60(3)
Use Case 5 Data Observability
63(8)
8 Two Cornerstones of a Data Fabric
71(10)
Examples of the Value of a Data Catalog
71(3)
Data Virtualization
74(7)
9 How IBM Delivers Value Through the Data Fabric
81(24)
Use Case 1 Data Governance and Privacy
85(6)
Use Case 2 Customer-360
91(3)
Use Case 3 MLOps and Trustworthy AI
94(7)
Use Case 4 Multicloud Data Integration
101(4)
10 Conclusion
105(4)
Appendix A Different Types of Data Storage Paradigms 109(9)
Notices and Disclaimers 118