Description

As organizations scale, the need for efficient and intelligent data platforms continues to grow. Azure Databricks stands out as a leading platform to deliver scalable data processing, collaborative workflows, and seamless cloud integration. The ability to build scalable pipelines using Apache Spark has become a critical skill for modern data professionals. This book provides a practical and structured journey through the complete data engineering lifecycle using Azure Databricks.

It begins with the fundamentals of big data and Spark, then moves into building scalable ETL/ELT pipelines, applying transformations, and enforcing data quality. You will explore architectural patterns in modern data ecosystems and build real-time streaming solutions. Readers will also learn to integrate Databricks with ADF, Power BI, Event Hubs, and other services. The book also covers DevOps and CI/CD using Databricks Asset Bundles.

By the end of this book, you will be equipped with the hands-on skills needed to design, build, validate, and manage production-grade data solutions on Azure Databricks. Whether you are a beginner or an experienced professional, you will gain the confidence to engineer robust data solutions that power analytics, AI, and modern data products.