Includes index.

Includes bibliographical references and index.

Part I. Self-service data delivery. Metadata catalog service ; Search service ; Feature story service ; Data movement service ; Clickstream tracking service -- Part II. Self-service data prep. Data lake management service ; Data wrangling service ; Data rights governance service -Part III. Self-service build. Data virtualization service ; Data transformations service ; Model training service ; Continuous integration service ; A/B testing service -- Part IV. Self-service operationalize. Query optimization service ; Pipeline orchestration service ; Model deploy service ; Quality observability service ; Cost management service.

"Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks. Most organizations can't scale data science teams fast enough to keep up with the growing amounts of data to transform. What's the answer? Self-service data. With this practical book, data engineers, data scientists, and team managers will learn how to build a self-service data science platform that helps anyone in your organization extract insights from data. Sandeep Uttamchandani provides a scorecard to track and address bottlenecks that slow down time to insight across data discovery, transformation, processing, and production. This book bridges the gap between data scientists bottlenecked by engineering realities and data engineers unclear about ways to make self-service work."--Publisher's description