Mastering Azure Databricks for Data Engineers will provide you with the in-depth knowledge and practical skills needed to work with Azure Databricks, a leading platform for data engineering tasks. By the end of the course, you will gain expertise in setting up and utilizing Databricks services, managing data workflows, and using Delta Lake and Databricks tools for efficient data engineering.
The course begins with an introduction to data engineering concepts, followed by a deep dive into the Databricks platform. You'll learn how to set up an Azure cloud account, create Databricks workspaces, and explore Databricks architecture. You'll also get hands-on experience creating Spark clusters and working with notebooks.
Throughout the course, you’ll learn how to work with Databricks File System (DBFS) and Unity Catalog, along with performing various operations on Delta Tables, such as time travel and schema evolution. The focus will also be on Databricks' incremental ingestion tools and Delta Live Tables (DLT), providing you with a comprehensive understanding of how to handle large-scale data ingestion and processing in real-time.
This course is perfect for data engineers and professionals who want to deepen their knowledge of data engineering platforms, particularly those using Azure Databricks. A basic understanding of data engineering and cloud platforms is recommended, but the course is structured to guide you from fundamental concepts to advanced implementations.
Applied Learning Project
The course includes a comprehensive capstone project that simulates real-world data engineering tasks. You'll design data architectures using Azure Databricks, focusing on setting up workspaces, creating Delta Tables, and automating data workflows. The project will require you to implement secure, efficient data ingestion processes and optimize performance with advanced features like Delta Live Tables and CI/CD pipelines.
