IBM® watsonx™ is a portfolio of AI products that accelerates the impact of generative AI in core workflows to drive productivity. This book focuses on watsonx.data, one of the three main components of the platform.

IBM watsonx.data is a hybrid, open data lakehouse to power AI and analytics with all your data, anywhere. Built on an open lakehouse architecture, it is optimized for governing data and AI workloads. Its capabilities include querying, governance, and support for open data formats, enabling easy data access and sharing.

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