Mastering Data Engineering and Analytics with Databricks

Master Databricks to Transform Data into Strategic Insights for Tomorrow’s Business Challenges


Book Description

In 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 Contents

SECTION 1

1. Introducing Data Engineering with Databricks

2. Setting Up a Databricks Environment for Data Engineering

3. Working with Databricks Utilities and Clusters

SECTION 2

4. Extracting and Loading Data Using Databricks

5. Transforming Data with Databricks

6. Handling Streaming Data with Databricks

7. Creating Delta Live Tables

8. Data Partitioning and Shuffling

9. Performance Tuning and Best Practices

10. Workflow Management

11. Databricks SQL Warehouse

12. Data Storage and Unity Catalog

13. Monitoring Databricks Clusters and Jobs

14. Production Deployment Strategies

15. Maintaining Data Pipelines in Production

16. Managing Data Security and Governance

17. Real-World Data Engineering Use Cases with Databricks

18. AI and ML Essentials

19. Integrating Databricks with External Tools

      Index