Databricks - Master Azure Databricks for Data Engineers

Learn Azure Databricks for professional data engineers using PySpark and Spark SQL with an end-to-end capstone project

About the Course

I am creating Databricks - Master Azure Databricks for Data Engineers using the Azure cloud platform. This course will help you learn the following things.

1. Databricks in Azure Cloud

2. Working with DBFS and Mounting Storage

3. Unity Catalog - Configuring and Working

4. Unity Catalog User Provisioning and Security

5. Working with Delta Lake and Delta Tables

6. Manual and Automatic Schema Evolution

7. Incremental Ingestion into Lakehouse

8. Databricks Autoloader

9. Delta Live Tables and DLT Pipelines

10. Databricks Repos and Databricks Workflow

11. Databricks Rest API and CLI

Capstone Project

This course also includes an End-To-End Capstone project. The project will help you understand the real-life project design, coding, implementation, testing, and CI/CD approach.

Who should take this Course?

I designed this course for data engineers who are willing to develop Lakehouse projects following the Medallion architecture approach using the Databrick cloud platform. I am also creating this course for data and solution architects responsible for designing and building the organization’s Lakehouse platform infrastructure. Another group of people is the managers and architects who do not directly work with Lakehouse implementation. Still, they work with those implementing Lakehouse at the ground level.

Spark Version used in the Course.

This course uses Databricks in Azure Cloud and Apache Spark 3.5. I have tested all the source codes and examples used in this course on Azure Databricks Cloud using Databricks Runtime 13.3.