Published on 30 January 2025, updated 31 January 2025
ISBN-10: 0738461954
ISBN-13: 9780738461953
IBM Form #: SG24-8570-00
Authors: Deepak Rangarao, Daniele Comi, Gopi Varadarajulu, Jun Liu, Karen Medhat, Malcolm Singh, Mark Simmonds, Payal Patel, Prabh Matharu, Saurabh Kaushik, Sreenath Devireddy, Ugur Ozker and Vasfi Gucer
IBM® watsonx™ is IBM’s strategic AI and Data platform. This book focuses on watsonx.data, one of the three main components of the platform.
IBM watsonx.data is a fit-for-purpose data store built on an open lakehouse architecture that is optimized for governed data and AI workloads, supported by querying, governance, and open data formats to access and share data. The solution can manage workloads both on premises and across hybrid multi-cloud environments while leveraging internal and external data sets. Through workload optimization, with this solution an organization can reduce data warehouse costs by up to 50 percent. It enables users to access robust data through a single point of entry while applying multiple fit-for-purpose query engines to uncover valuable insights. It also provides built-in data governance tools, automation, and integration with an organization's existing databases and tools to simplify setup and the user experience.
This IBM Redbooks® publication provides a broad understanding of watsonx.data concepts and architecture, and the services that are available in the product. In addition, several common use cases and scenarios are included that should help you better understand the capabilities of this product.
This publication is for watsonx customers who seek best practices and real-world examples of how to best implement their solutions while optimizing the value of their existing and future technology, AI, data, and skills investments.
Foreword
Chapter 1. Challenges and opportunities with data
Chapter 2. Introduction to IBM watsonx.data
Chapter 3. Ingesting data into an open data lakehouse
Chapter 4. Protecting data
Chapter 5. Querying and manipulating data and leveraging persona-specific engines
Chapter 6. Establishing data governance
Chapter 7. Establishing a data catalog
Chapter 8. Marketing campaign analysis use case
Chapter 9. Adopting Milvus for RAG using IBM watsonx
Chapter 10. Data and AI modernization strategy in banking use case