Data Engineering with Databricks Cookbook
Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake
Created by Pulkit Chadha
Explore practical ways to build and manage data pipelines using Apache Spark, Databricks, and Delta Lake. Gain hands-on experience with data ingestion, transformation, and workflow orchestration while learning to optimize performance and enforce data governance.
Packt | May 2024 | 438 min
What You Will Learn
You will work through real-world scenarios that guide you from ingesting and transforming data to managing and optimizing data pipelines. Step-by-step examples help you apply DataOps and DevOps practices, orchestrate workflows, and enforce governance using Unity Catalog. Each section builds your confidence with practical, actionable techniques.
Key Features
- Master data ingestion and transformation with Apache Spark and Delta Lake
- Optimize performance and manage Delta tables for scalable pipelines
- Implement DataOps, DevOps, and data governance on Databricks
Target Audience
Ideal for data engineers, data scientists, and technical professionals with a basic understanding of data architecture, SQL, and Python. If you want to create efficient, scalable data solutions using modern tools and best practices, you'll find clear guidance to advance your skills and deliver reliable data pipelines.
