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.Build a self-service portal to support data discovery, quality, lineage, and governanceSelect the best approach for each self-service capability using open source cloud technologiesTailor self-service for the people, processes, and technology maturity of your data platformImplement capabilities to democratize data and reduce time to insightScale your self-service portal to support a large number of users within your organization
Daugiau prekių iš šios kategorijos
- Importance of Data-Driven Insights: In today’s competitive landscape, harnessing insights from data provides a crucial edge, but extracting these insights can be time-consuming and challenging at scale.
What is the primary focus of the book on self-service data platforms?
The book focuses on guiding readers to build a self-service data science platform that enables anyone in an organization to extract insights from data efficiently.








