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

Introducing Data Operations (DataOps)

Data is the fuel for innovation and sustaining a competitive advantage. It is the key ingredient for driving analytics and understanding business trends and opportunities. Unlocking this value in new ways can accelerate an organization's journey to AI.

DataOps is focused on enabling collaboration across an organization to drive agility, speed, and new data initiatives at scale. By using the power of automation, DataOps is designed to solve challenges associated with inefficiencies in accessing, preparing, integrating, and making data available.

At the core of DataOps is an organization's information architecture, which addresses the following questions:

  • Do you know your data? Do you trust your data?
  • Are you able to quickly detect errors?
  • Can you make changes incrementally without "breaking" your entire data pipeline?

To answer all these questions, the first step is to take inventory of your...