Implement a Data Analytics Solution with Azure Databricks (DP-3011)

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 wi...

Explore Azure Databricks


- Introduction
- Get started with Azure Databricks
- Identify Azure Databricks workloads
- Understand key concepts
- Data governance using Unity Catalog and Microsoft Purview
- Exercise - Explore Azure Databricks
- Module assessment
- Summary

Perform data analysis with Azure Databricks


- Introduction
- Ingest data with Azure Databricks
- Data exploration tools in Azure Databricks
- Data analysis using DataFrame APIs
- Exercise - Explore data with Azure Databricks
- Module assessment
- Summary

Use Apache Spark in Azure Databricks


- Introduction
- Get to know Spark
- Create a Spark cluster
- Use Spark in notebooks
- Use Spark to work with data files
- Visualize data
- Exercise - Use Spark in Azure Databricks
- Module assessment
- Summary

Manage data with Delta Lake


- Introduction
- Get started with Delta Lake
- Create Delta tables
- Implement schema enforcement
- Data versioning and time travel in Delta Lake
- Data integrity with Delta Lake
- Exercise - Use Delta Lake in Azure Databricks
- Module assessment
- Summary

Build Lakeflow Declarative Pipelines


- Introduction
- Explore Lakeflow Declarative Pipelines
- Data ingestion and integration
-...

​Before taking this course, learners should already be comfortable with the fundamentals of Python and SQL. This includes being able to write simple Python scripts and work with common data structures, as well as writing SQL queries to filter, join, and aggregate data. A basic understanding of common file formats such as CSV, JSON, or Parquet will also help when working with datasets.
In addition, familiarity with the Azure portal and core services like Azure Storage is important, along with...