Microsoft Fabric Analytics Engineer

This course is best suited for those who have the PL-300 certification or similar expertise in using Power BI for data transformation, modeling, visualization, and sharing. Also, learners should have prior experience in building and deploying data analytics solutions at the enterprise level.

• Describe Dataflow (Gen2) capabilities in Microsoft Fabric
• Create Dataflow (Gen2) solutions to ingest and transform data
• Include a Dataflow (Gen2) in a pipeline

• 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
• Summary

• Ingest external data to Fabric lakehouses using Spark
• Configure external source authentication and optimization
• Load data into lakehouse as files or as Delta tables

• 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
• Summary

• Describe pipeline capabilities in Microsoft Fabric
• Use the Copy Data activity in a pipeline
• Create pipelines based on predefined templates
• Run and monitor pipelines

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

• Describe core features and capabilities of lakehouses in Microsoft Fabric
• Create a lakehouse
• Ingest data into files and tables in a lakehouse
• Query lakehouse tables with SQL

• 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
• Summary

• Describe the principles of using the medallion architecture in data management.
• Apply the medallion architecture framework within the Microsoft Fabric environment.
• Analyze data stored in the lakehouse using DirectLake in Power BI.
• Describe best practices for ensuring the security and governance of data stored in the medallion architecture.

• 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
• Summary

• Configure Spark in a Microsoft Fabric workspace
• Identify suitable scenarios for Spark notebooks and Spark jobs
• Use Spark dataframes to analyze and transform data
• Use Spark SQL to query data in tables and views
• Visualize data in a Spark notebook

• 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
• Summary

• Understand Delta Lake and delta tables in Microsoft Fabric
• Create and manage delta tables using Spark
• Use Spark to query and transform data in delta tables
• Use delta tables with Spark structured streaming

• 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
• Summary

• Describe data warehouses in Fabric
• Understand a data warehouse vs a data Lakehouse
• Work with data warehouses in Fabric
• Create and manage datasets within a data warehouse

• 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
• Summary

• Learn different strategies to load data into a data warehouse in Microsoft Fabric.
• Learn how to build a data pipeline to load a warehouse in Microsoft Fabric.
• Learn how to load data in a warehouse using T-SQL.
• Learn how to load and transform data with dataflow (Gen 2).

• 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
• Summary

• Use SQL query editor to query a data warehouse.
• Explore how visual query editor works.
• Learn how to connect and query a data warehouse using SQL Server Management Studio.

• 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
• Summary

• Monitor capacity unit usage with the Microsoft Fabric Capacity Metrics app.
• Monitor current activity in the data warehouse with dynamic management views.
• Monitor querying trends with query insights views.

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

• Describe the importance of building scalable data models
• Implement Power BI data modeling best practices
• Use the Power BI large dataset storage format

• 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
• Summary

• Understand how model relationship work.
• Set up relationships.
• Use DAX relationship functions.
• Understand relationship evaluation.

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

• Optimize queries using performance analyzer.
• Troubleshoot DAX performance using DAX Studio.
• Optimize a data model using Tabular Editor.

• 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
• Summary

• Restrict access to Power BI model data with RLS.
• Restrict access to Power BI model objects with OLS.
• Apply good development practices to 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
• Summary