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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

Summary

Data is the world's most valuable resource and to be successful, enterprises need to become data-centric and leverage their data as a key differentiator. However, increasing data volumes, evolving data stores, and distributed datasets are making it difficult for enterprises and business users to easily find and access the data they need. Today's enterprise data architecture is fairly complex, with a plethora of data stores optimized for specific workloads. Data virtualization offers the silver bullet to address this unique challenge, and IBM's Cloud Pak Data is one of the key vendors in the market today. It is differentiated for its ability to scale and its integrated approach, which addresses data management, data organization, and data analysis requirements.

Finally, IBM's Cloud Pak for Data complements its data virtualization service with several containerized data stores that allow customers to persist data on the platform, while also allowing them...

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