Book Image

IBM Cloud Pak for Data

By : Hemanth Manda, Sriram Srinivasan, Deepak Rangarao
3 (1)
Book Image

IBM Cloud Pak for Data

3 (1)
By: Hemanth Manda, Sriram Srinivasan, Deepak Rangarao

Overview of this book

Cloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services. You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects. By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise.

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Table of Contents (17 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the color images
Conventions used
Get in touch
Share Your Thoughts
1
Section 1: The Basics
Section 1: The Basics
Free Chapter
2
Chapter 1: The AI Ladder – IBM's Prescriptive Approach
Chapter 1: The AI Ladder – IBM's Prescriptive Approach
Market dynamics and IBM's Data and AI portfolio
Introduction to the AI ladder
Collect – making data simple and accessible
Organize – creating a trusted analytics foundation
Analyze – building and scaling models with trust and transparency
Infuse – operationalizing AI throughout the business
Summary
3
Chapter 2: Cloud Pak for Data: A Brief Introduction
Chapter 2: Cloud Pak for Data: A Brief Introduction
The case of a data and AI platform – recap
Overview of Cloud Pak for Data
Exploring unique differentiators, key use cases, and customer adoption
Cloud Pak for Data: additional details
Red Hat OpenShift
Summary
4
Section 2: Product Capabilities
Section 2: Product Capabilities
5
Chapter 3: Collect – Making Data Simple and Accessible
Chapter 3: Collect – Making Data Simple and Accessible
Data – the world's most valuable asset
Challenges with data-centric delivery
Enterprise data architecture
Data virtualization – accessing data anywhere
Data virtualization versus ETL – when to use what?
Platform connections – streamlining data connectivity
Data estate modernization using Cloud Pak for Data
Summary
6
Chapter 4: Organize – Creating a Trusted Analytics Foundation
Chapter 4: Organize – Creating a Trusted Analytics Foundation
Introducing Data Operations (DataOps)
Organizing enterprise information assets
Establishing metadata and stewardship
Profiling to get a better understanding of your data
Classifying data for completeness
Enabling trust with data quality
Data privacy and activity monitoring
Data integration at scale
Master data management
Extending MDM toward a Digital Twin
Summary
7
Chapter 5: Analyzing: Building, Deploying, and Scaling Models with Trust and Transparency
Chapter 5: Analyzing: Building, Deploying, and Scaling Models with Trust and Transparency
Self-service analytics of governed data
BI and reporting
Predictive versus prescriptive analytics
Understanding AI
AI life cycle – Transforming insights into action
AI governance: Trust and transparency
Automating the AI life cycle using Cloud Pak for Data
Summary
8
Chapter 6: Multi-Cloud Strategy and Cloud Satellite
Chapter 6: Multi-Cloud Strategy and Cloud Satellite
IBM's multi-cloud strategy
Supported deployment options
Cloud Pak for Data as a Service
IBM Cloud Satellite
A data fabric for a multi-cloud future
Summary
9
Chapter 7: IBM and Partner Extension Services
Chapter 7: IBM and Partner Extension Services
IBM and third-party extension services
Collect extension services
Organize extension services
Infuse cartridges
Modernization upgrades to Cloud Pak for Data cartridges
Summary
10
Chapter 8: Customer Use Cases
Chapter 8: Customer Use Cases
Improving health advocacy program efficiency
Voice-enabled chatbots
Risk and control automation
Enhanced border security
Unified Data Fabric
Financial planning and analytics
Summary
11
Section 3: Technical Details
Section 3: Technical Details
12
Chapter 9: Technical Overview, Management, and Administration
Chapter 9: Technical Overview, Management, and Administration
Technical requirements
Architecture overview
Infrastructure requirements, storage, and networking
Foundational services and the control plane
Multi-tenancy, resource management, and security
Day 2 operations
Summary
References
13
Chapter 10: Security and Compliance
Chapter 10: Security and Compliance
Technical requirements
Security and Privacy by Design
Secure operations in a shared environment
User access and authorizations
Meeting compliance requirements
Summary
References
14
Chapter 11: Storage
Chapter 11: Storage
Understanding the concept of persistent volumes
Off-cluster storage
Operational considerations
Summary
Further reading
15
Chapter 12: Multi-Tenancy
Chapter 12: Multi-Tenancy
Tenancy considerations
Architecting for multi-tenancy
Reviewing the tenancy requirements
In-namespace sub-tenancy with looser isolation
Summary
Why subscribe?
16
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Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "The Cloud Pak for Data control plane introduces a special persistent volume claim called user-home-pvc."

A block of code is set as follows:

kubectl get pvc user-home-pvc
NAME            STATUS   VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS   AGE
user-home-pvc   Bound    pvc-44e5a492-9921-41e1-bc42-b96a9a4dd3dc   10Gi       RWX            nfs-client     33d

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

Port:              zencoreapi-tls  4444/TCP
TargetPort:        4444/TCP
Endpoints:         10.254.16.52:4444,10.254.20.23:4444

Bold: Indicates a new term, an important word, or words that you see on screen. For instance, words in menus or dialog boxes appear in bold. Here is an example: "There are essentially two types of host nodes (as presented in the screenshot) – the Master and Compute (worker) nodes."

Tips or important notes

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