This course provides in-depth training on implementing and managing large-scale data analytics solutions using Microsoft Fabric. Participants will learn how to utilize Fabric dataflows, pipelines, and notebooks to build analytics assets, including semantic models, data warehouses, and lakehouses. Designed for experienced data professionals with skills in data preparation, modelling, analysis, and visualization (e.g., those with PL-300: Power BI Data Analyst certification), the course requires prior knowledge of programming languages such as SQL, KQL, or DAX.
Course Outline
Lesson 1: Get started with Microsoft Fabric
- Introduction to end-to-end analytics using Microsoft Fabric
- Introduction
- Explore end-to-end analytics with Microsoft Fabric
- Data teams and Microsoft Fabric
- Enable and use Microsoft Fabric
- Knowledge Check
- Summary
- 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
- Summary
- Use Apache Spark in Microsoft Fabric
- Introduction
- Prepare to use Apache Spark
- Run Spark code
- Connect to data sources and ingest data
- 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
- Work with Delta Lake tables in Microsoft Fabric
- Introduction
- Understand Delta Lake
- Create delta tables
- 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
- Orchestrate processes and data movement with 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
- Summary
- 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
- Summary
- 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
- Summary
- Get started with Real-Time Intelligence in Microsoft Fabric
- Introduction
- Describe Microsoft Fabric Real-Time Intelligence?
- Understand KQL database and tables
- Describe Microsoft Fabric Real-Time hub
- Write queries with KQL
- Exercise: Explore Real-Time Intelligence in Fabric
- Knowledge check
- Summary
- Get started with data science in Microsoft Fabric
- Introduction
- Understand the data science process
- Explore and process data with Microsoft Fabric
- Train and score models with Microsoft Fabric
- Exercise – Explore data science in Microsoft Fabric
- Knowledge check
- Summary
- Get started with Data Activator in Microsoft Fabric
- Introduction
- Understand Data Activator
- Get started with Data Activator
- Understand triggers, conditions and actions in Data Activator
- Get data from Power BI Reports and EventStreams with Data Activator
- Assign data in Data Activator
- Create triggers in Data Activator
- Exercise – Use Data Activator in Fabric
- Knowledge check
- Summary
- Administer a Microsoft Fabric environment
- Introduction
- Understand the Fabric Architecture
- Understand the Fabric administrator role
- Manage Fabric security
- Govern data in Fabric
- Knowledge check
- Summary
Lesson 2: Implement a data warehouse with Microsoft Fabric
- 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
- Summary
- 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
- Summary
- Query a data warehouse in Microsoft Fabric
- Introduction
- Query data
- 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 a Microsoft Fabric data warehouse
- Introduction
- Monitor capacity metrics
- Monitor current activity
- Monitor queries
- Exercise – Monitor a data warehouse in Microsoft Fabric
- Knowledge check
- Summary
- Secure a Microsoft Fabric data warehouse
- Introduction
- Explore dynamic data masking
- Implement row-level security
- Implement column-level security
- Configure SQL granular permissions using T-SQL
- Exercise: Secure a warehouse in Microsoft Fabric
- Knowledge check
- Summary
Lesson 3: Work with semantic models in Microsoft Fabric
- Add measures to Power BI Desktop models:
- Create simple measures
- Create compound measures
- Create quick measures
- Compare calculated columns with measures
- Check your knowledge
- Exercise – Create DAX Calculations in Power BI Desktop
- Design scalable semantic models:
- Choose the best storage mode
- Configure semantic models for large data
- Work with relationships
- Write DAX for readability with complex calculations
- Create dynamic calculation elements
- Exercise – Design a scalable semantic model
- Optimize a model for performance in Power BI:
- Introduction to performance optimization
- Review performance of measures, relationships, and visuals
- Use variables to improve performance and troubleshooting
- Reduce cardinality
- Optimize DirectQuery models with table level storage
- Create and manage aggregations
- Use tools to optimize Power BI performance:
- 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
- Create and manage Power BI assets:
- Create reusable Power BI assets
- Manage development lifecycle for Power BI assets
- Use lineage view and endorse data assets
- Manage a Power BI semantic model using XMLA endpoint
- Exercise: Create reusable Power BI assets
- Enforce Power BI model security:
- Restrict access to Power BI model data
- Restrict access to Power BI model objects
- Apply good modeling practices
- Exercise: Enforce model security
Lesson 4: Administer and govern Microsoft Fabric
- Administer a Microsoft Fabric environment:
- Understand the Fabric Architecture
- Understand the Fabric administrator role
- Manage Fabric security
- Govern data in Fabric
- Secure a Microsoft Fabric data warehouse:
- Explore dynamic data masking
- Implement row-level security
- Implement column-level security
- Configure SQL granular permissions using T-SQL
- Exercise: Secure a warehouse in Microsoft Fabric
- Govern data in Microsoft Fabric with Purview:
- Govern data in Microsoft Fabric
- Why use Microsoft Purview with Microsoft Fabric?
- Govern data in the Microsoft Purview hub
