IBM Cloud Pak for Data
Hemanth Manda, Sriram Srinivasan, Deepak Rangarao
- 336 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
IBM Cloud Pak for Data
Hemanth Manda, Sriram Srinivasan, Deepak Rangarao
About This Book
Build end-to-end AI solutions with IBM Cloud Pak for Data to operationalize AI on a secure platform based on cloud-native reliability, cost-effective multitenancy, and efficient resource managementKey Features⢠Explore data virtualization by accessing data in real time without moving it⢠Unify the data and AI experience with the integrated end-to-end platform⢠Explore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook DescriptionCloud 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.What you will learn⢠Understand the importance of digital transformations and the role of data and AI platforms⢠Get to grips with data architecture and its relevance in driving AI adoption using IBM's AI Ladder⢠Understand Cloud Pak for Data, its value proposition, capabilities, and unique differentiators⢠Delve into the pricing, packaging, key use cases, and competitors of Cloud Pak for Data⢠Use the Cloud Pak for Data ecosystem with premium IBM and third-party services⢠Discover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho this book is forThis book is for data scientists, data stewards, developers, and data-focused business executives interested in learning about IBM's Cloud Pak for Data. Knowledge of technical concepts related to data science and familiarity with data analytics and AI initiatives at various levels of maturity are required to make the most of this book.
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Section 1: The Basics
- Chapter 1, The AI Ladder: IBM's Prescriptive Approach
- Chapter 2, Cloud Pak for Data â A Brief Introduction
Chapter 1: The AI Ladder â IBM's Prescriptive Approach
- Market dynamics and IBM's Data and AI portfolio
- Introduction to the AI ladder
- Collect â making data simple and accessible
- Organize â creating a trusted analytics foundation
- Analyze â building and scaling AI with trust and transparency
- Infuse â operationalizing AI throughout the business
Market dynamics and IBM's Data and AI portfolio
Introduction to the AI ladder
The rungs of the AI ladder
- Collect: Make data simple and accessible. Collect data of every type regardless of where it lives, enabling flexibility in the face of ever-changing data sources.
- Organize: Create a business-ready analytics foundation. Organize all the client's data into a trusted, business-ready foundation with built-in governance, quality, protection, and compliance.
- Analyze: Build and scale AI with trust and explainability. Analyze the client's data in smarter ways and benefit from AI models that empower the client's team to gain new insights and make better, smarter decisions.
- Infuse: Operationalize AI throughout the business. You should do this across multiple departments and within various processes by drawing on predictions, automation, and optimization. Craft an effective AI strategy to realize your AI business objectives. Apply AI to automate and optimize existing workflows in your business, allowing your employees to focus on higher-value work.