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.
Table of Contents (17 chapters)
Section 1: The Basics
Section 2: Product Capabilities
Section 3: Technical Details

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...