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

Learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run large data engineering workloads in the cloud.

Module 1 : Explore Azure Databricks

• Provision an Azure Databricks workspace.
• Identify core workloads and personas for Azure Databricks.
• Describe key concepts of an Azure Databricks solution.

Module 2 : Use Apache Spark in Azure Databricks

• Describe key elements of the Apache Spark architecture.
• Create and configure a Spark cluster.
• Describe use cases for Spark.
• Use Spark to process and analyze data stored in files.
• Use Spark to visualize data.

Module 3 : Use Delta Lake in Azure Databricks

• Describe core features and capabilities of Delta Lake.
• Create and use Delta Lake tables in Azure Databricks.
• Create Spark catalog tables for Delta Lake data.
• Use Delta Lake tables for streaming data.

Module 4 : Use SQL Warehouses in Azure Databricks

• Create and configure SQL Warehouses in Azure Databricks.
• Create databases and tables.
• Create queries and dashboards.

Module 5 : Run Azure Databricks Notebooks with Azure Data Factory

• Describe how Azure Databricks notebooks can be run in a pipeline.
• Create an Azure Data Factory linked service for Azure Databricks.
• Use a Notebook activity in a pipeline.
• Pass parameters to a notebook.

Students willing to Implement a Data Analytics Solution with Azure Databricks.