Our lesson provides a practical guide to effectively utilizing Apache Spark, Delta Lake, and Databricks for data engineering. It begins with a thorough introduction to data ingestion and loading using Apache Spark. What sets this lesson apart is its recipe-based format, which enables you to immediately apply your knowledge and address common challenges.
You’ll explore various techniques for data manipulation and transformation, learn how to manage and optimize Delta tables, and understand the process of ingesting and processing streaming data. Additionally, the book addresses performance issues associated with Apache Spark applications and Delta Lake.
Later sections introduce advanced tech-recipes that demonstrate how to implement DataOps and DevOps practices using Databricks, as well as how to orchestrate and schedule data pipelines with Databricks Workflows. Furthermore, my lesson guides you through the complete setup and configuration of the Unity Catalog for data governance. By the conclusion of this lesson, you will be proficient in constructing reliable and scalable data pipelines using contemporary data engineering technologies.
Data Engineering with Databricks Cookbook
By : Pulkit Chadha
Curriculum
- 1 Section
- 4 Lessons
- 10 Weeks
