This course explores how to use Databricks and Apache Spark on Azure to take data projects from exploration to production. You’ll learn how to ingest, transform, and analyze large-scale datasets with Spark DataFrames, Spark SQL, and PySpark, while also building confidence in managing distributed data processing jobs at scale. The course prepares you for the DP-3011 Microsoft Applied Skills credential.
Who Should Attend
Data Engineers, Data Analysts, and Azure professionals who need to implement data engineering solutions using Azure Databricks and Apache Spark.
Prerequisites
- Familiarity with Python programming
- Basic understanding of data engineering concepts
- Experience with Azure data services is beneficial
Course Objectives
- Configure and manage Azure Databricks workspaces and clusters
- Ingest and transform data using Spark DataFrames and Spark SQL
- Implement Delta Lake for reliable data lake operations
- Build and orchestrate data pipelines using Databricks workflows
