The primary audience for this course is data professionals with experience in data modeling, extraction, and analytics. DP-600 is designed for professionals who want to use Microsoft Fabric to create and deploy enterprise-scale data analytics solutions.
 

Ingest Data with Dataflows Gen2 in Microsoft Fabric

• Introduction
• Understand Dataflows Gen2 in Microsoft Fabric
• Explore Dataflows Gen2 in Microsoft Fabric
• Integrate Dataflows Gen2 and Pipelines in Microsoft Fabric
• Exercise – Create and use a Dataflow Gen2 in Microsoft Fabric
• Knowledge check

Ingest data with Spark and Microsoft Fabric notebooks

• Introduction
• Connect to data with Spark
• Write data into a lakehouse
• Consider uses for ingested data
• Exercise – Ingest data with Spark and Microsoft Fabric notebooks
• Knowledge check

Use Data Factory pipelines in Microsoft Fabric

• Introduction
• Understand pipelines
• Use the Copy Data activity
• Use pipeline templates
• Run and monitor pipelines
• Exercise – Ingest data with a pipeline
• Knowledge check

Get started with lakehouses in Microsoft Fabric

• Introduction
• Explore the Microsoft Fabric Lakehouse
• Work with Microsoft Fabric Lakehouses
• Explore and transform data in a lakehouse
• Exercise – Create and ingest data with a Microsoft Fabric Lakehouse
• Knowledge check

Organize a Fabric lakehouse using medallion architecture design

• Introduction
• Describe medallion architecture
• Implement a medallion architecture in Fabric
• Query and report on data in your Fabric lakehouse
• Considerations for managing your lakehouse
• Exercise – Organize your Fabric lakehouse using a medallion architecture
• Knowledge check

Use Apache Spark in Microsoft Fabric

• Introduction
• Prepare to use Apache Spark
• Run Spark code
• Work with data in a Spark dataframe
• Work with data using Spark SQL
• Visualize data in a Spark notebook
• Exercise – Analyze data with Apache Spark
• Knowledge check

Work with Delta Lake tables in Microsoft Fabric

• Introduction
• Understand Delta Lake
• Create delta tables
• Work with delta tables in Spark
• Use delta tables with streaming data
• Exercise – Use delta tables in Apache Spark
• Knowledge check

Get started with data warehouses in Microsoft Fabric

• Introduction
• Understand data warehouse fundamentals
• Understand data warehouses in Fabric
• Query and transform data
• Prepare data for analysis and reporting
• Secure and monitor your data warehouse
• Exercise – Analyze data in a data warehouse
• Knowledge check

Load data into a Microsoft Fabric data warehouse

• Introduction
• Explore data load strategies
• Use data pipelines to load a warehouse
• Load data using T-SQL
• Load and transform data with Dataflow Gen2
• Exercise: Load data into a warehouse in Microsoft Fabric
• Knowledge check

Query a data warehouse in Microsoft Fabric

• Introduction
• Use the SQL query editor
• Explore the visual query editor
• Use client tools to query a warehouse
• Exercise: Query a data warehouse in Microsoft Fabric
• Knowledge check

Monitor a Microsoft Fabric data warehouse

• Introduction
• Monitor capacity metrics
• Monitor current activity
• Monitor queries
• Exercise – Monitor a data warehouse in Microsoft Fabric
• Knowledge check

Understand scalability in Power BI

• Introduction
• Describe the significance of scalable models
• Implement Power BI data modeling best practices
• Configure large datasets
• Exercise: Create a star schema model
• Knowledge check

Create Power BI model relationships

• Introduction
• Understand model relationships
• Set up relationships
• Use DAX relationship functions
• Understand relationship evaluation
• Exercise: Work with model relationships
• Knowledge check

Use tools to optimize Power BI performance

• Introduction
• Use Performance analyzer
• Troubleshoot DAX performance by using DAX Studio
• Optimize a data model by using Best Practice Analyzer
• Exercise: Use tools to optimize Power BI performance
• Knowledge check

Enforce Power BI model security

• Introduction
• Restrict access to Power BI model data
• Restrict access to Power BI model objects
• Apply good modeling practices
• Exercise: Enforce model security
• Knowledge check