
Mastering Data Engineering and Analytics with Databricks
A Hands-on Guide to Build Scalable Pipelines Using Databricks, Delta Lake, and MLflow (English Edition)
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Mastering Data Engineering and Analytics with Databricks
A Hands-on Guide to Build Scalable Pipelines Using Databricks, Delta Lake, and MLflow (English Edition)
About this book
Master Databricks to Transform Data into Strategic Insights for Tomorrow's Business Challenges
Book DescriptionIn today's data-driven world, mastering data engineering is crucial for driving innovation and delivering real business impact. Databricks is one of the most powerful platforms which unifies data, analytics and AI requirements of numerous organizations worldwide.
Mastering Data Engineering and Analytics with Databricks goes beyond the basics, offering a hands-on, practical approach tailored for professionals eager to excel in the evolving landscape of data engineering and analytics.
This book uniquely blends foundational knowledge with advanced applications, equipping readers with the expertise to build, optimize, and scale data pipelines that meet real-world business needs. With a focus on actionable learning, it delves into complex workflows, including real-time data processing, advanced optimization with Delta Lake, and seamless ML integration with MLflow—skills critical for today's data professionals.
Table of ContentsSECTION 11. Introducing Data Engineering with Databricks2. Setting Up a Databricks Environment for Data Engineering3. Working with Databricks Utilities and ClustersSECTION 24. Extracting and Loading Data Using Databricks5. Transforming Data with Databricks6. Handling Streaming Data with Databricks7. Creating Delta Live Tables8. Data Partitioning and Shuffling9. Performance Tuning and Best Practices10. Workflow Management11. Databricks SQL Warehouse12. Data Storage and Unity Catalog13. Monitoring Databricks Clusters and Jobs14. Production Deployment Strategies15. Maintaining Data Pipelines in Production16. Managing Data Security and Governance17. Real-World Data Engineering Use Cases with Databricks18. AI and ML Essentials19. Integrating Databricks with External Tools Index
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Information
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Dedication Page
- About the Author
- About the Technical Reviewers
- Acknowledgements
- Preface
- Get a Free eBook
- Errata
- Table of Contents
- SECTION 1 Getting Started with Data Engineering and Databricks
- SECTION 2 Building Robust Data Pipelines with Databricks
- Index