Zakres

• 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
• Get started with lakehouses in Microsoft Fabric
  • 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
• Use Apache Spark in Microsoft Fabric
  • 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
• Work with Delta Lake tables in Microsoft Fabric
  • 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
• Ingest Data with Dataflows Gen2 in Microsoft Fabric
  • 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
• Use Data Factory pipelines in Microsoft Fabric
  • Understand pipelines
  • Use the Copy Data activity
  • Use pipeline templates
  • Run and monitor pipelines
  • Exercise – Ingest data with a pipeline
• Organize a Fabric lakehouse using medallion architecture design
  • 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

Ingest data with Microsoft Fabric

• Ingest Data with Dataflows Gen2 in Microsoft Fabric
  • 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
• Ingest data with Spark and Microsoft Fabric notebooks
  • Connect to data with Spark
  • Write data into a lakehouse
  • Consider uses for ingested data
  • Exercise – Ingest data with Spark and Microsoft Fabric notebooks
• Use Data Factory pipelines in Microsoft Fabric
  • Understand pipelines
  • Use the Copy Data activity
  • Use pipeline templates
  • Run and monitor pipelines
  • Exercise – Ingest data with a pipeline

Implement a data warehouse with Microsoft Fabric

• Get started with data warehouses in Microsoft Fabric
  • 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
• Load data into a Microsoft Fabric data warehouse
  • 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
• Query a data warehouse in Microsoft Fabric
  • 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
• Monitor a Microsoft Fabric data warehouse
  • Monitor capacity metrics
  • Monitor current activity
  • Monitor queries
  • Exercise – Monitor a data warehouse in Microsoft 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

Work with semantic models in Microsoft Fabric

• Understand scalability in Power BI
  • Describe the significance of scalable models
  • Implement Power BI data modeling best practices
  • Configure large datasets
• Create Power BI model relationships
  • Understand model relationships
  • Set up relationships
  • Use DAX relationship functions
  • Understand relationship evaluation
  • Exercise: Work with model relationships
• 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
• 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

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