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IBM Cloud Pak for Data

You're reading from   IBM Cloud Pak for Data An enterprise platform to operationalize data, analytics, and AI

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Product type Paperback
Published in Nov 2021
Publisher Packt
ISBN-13 9781800562127
Length 336 pages
Edition 1st Edition
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Authors (3):
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Hemanth Manda Hemanth Manda
Author Profile Icon Hemanth Manda
Hemanth Manda
Sriram Srinivasan Sriram Srinivasan
Author Profile Icon Sriram Srinivasan
Sriram Srinivasan
Deepak Rangarao Deepak Rangarao
Author Profile Icon Deepak Rangarao
Deepak Rangarao
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: The Basics
2. Chapter 1: The AI Ladder – IBM's Prescriptive Approach FREE CHAPTER 3. Chapter 2: Cloud Pak for Data: A Brief Introduction 4. Section 2: Product Capabilities
5. Chapter 3: Collect – Making Data Simple and Accessible 6. Chapter 4: Organize – Creating a Trusted Analytics Foundation 7. Chapter 5: Analyzing: Building, Deploying, and Scaling Models with Trust and Transparency 8. Chapter 6: Multi-Cloud Strategy and Cloud Satellite 9. Chapter 7: IBM and Partner Extension Services 10. Chapter 8: Customer Use Cases 11. Section 3: Technical Details
12. Chapter 9: Technical Overview, Management, and Administration 13. Chapter 10: Security and Compliance 14. Chapter 11: Storage 15. Chapter 12: Multi-Tenancy 16. Other Books You May Enjoy

Data estate modernization using Cloud Pak for Data

So far, we have seen the evolving complexity of the data landscape and the challenges enterprises are trying to address. Increasing data volumes, expanding data stores, and hybrid multi-cloud deployment scenarios have made it very challenging to consolidate data for analysis. IBM's Cloud Pak for Data offers a very modern solution to this challenge. At its core is the data virtualization service, which lets customers tap into the data in source systems without moving the data. More importantly, its integration with the enterprise catalog means that any data that's accessed is automatically discovered, profiled, and cataloged for future searches. Customers can join data from multiple sources into virtualized views and can easily enforce governance and privacy policies, making it a one-stop shop for data access. Finally, its ability to scale and leverage source system resources is extremely powerful.

IBM's data virtualization...

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