Module 1: Introduction to end-to-end analytics using Microsoft Fabric
Discover how Microsoft Fabric can meet your enterprise's analytics needs in one platform. Learn about Microsoft Fabric, how it works, and identify how you can use it for your analytics needs.
Module 2: Discover and connect to data in OneLake
Browse and connect to data using Microsoft OneLake's unified storage. Discover data across workspaces with the OneLake catalog, create shortcuts to reference existing data, and explore streaming sources in Real-Time hub.
Module 3: Get started with lakehouses in Microsoft Fabric
Lakehouses in Microsoft Fabric combine data lake storage flexibility with data warehouse analytical capabilities. Learn how to create a lakehouse, ingest and transform data, and query data with SQL and Spark.
Module 4: Get started with data warehouses in Microsoft Fabric
Understand what a Fabric data warehouse is, why it provides full T-SQL transactional capabilities, and how to create, query, and transform data for analytics.
Module 5: Get started with Real-Time Intelligence in Microsoft Fabric
Real-Time Intelligence in Microsoft Fabric helps you ingest, process, store, visualize, and act on data in motion to get insights from events as they happen.
Module 6: Choose data stores in Microsoft Fabric
Evaluate lakehouse, warehouse, and eventhouse options to select the appropriate analytical data store for business scenarios in Microsoft Fabric.
Module 7: Design dimensional models for analytics in Microsoft Fabric
Learn dimensional schema types, fact and dimension table design, and slowly changing dimension patterns for analytics workloads in Microsoft Fabric.
Module 8: Transform data using Dataflows Gen2 in Microsoft Fabric
Apply low-code transformations using Power Query in Dataflows Gen2 to prepare analytical data for downstream consumption.
Module 9: Transform data using notebooks in Microsoft Fabric
Use Fabric notebooks to transform data with Spark SQL and PySpark, connecting to lakehouses, warehouses, and other data stores.
Module 10: Transform data using T-SQL in Microsoft Fabric
Use T-SQL in Microsoft Fabric warehouses to transform and query data, create reusable views and stored procedures, and build dimensional tables.
Module 11: Create DAX calculations in semantic models
Adding DAX calculations to Power BI semantic models allows you to define custom logic within your data model, to enable deeper analysis and data-driven business decisions.
Module 12: Design semantic models for scale in Microsoft Fabric
Design semantic models for scale in Microsoft Fabric. Choose the right storage mode, design star schema relationships for clarity and performance, create scalable calculation patterns, and configure settings that support large datasets and concurrent consumption.
Module 13: Optimize semantic model performance
Diagnose and fix semantic model and report performance issues. Use Performance analyzer to identify bottlenecks, optimize DAX calculations, reduce cardinality, and implement aggregations to improve query speed.
Module 14: Enforce semantic model security
Implement row-level security (RLS), object-level security (OLS), and dynamic security patterns to protect sensitive data in semantic models while enabling appropriate access for different user groups.
Module 15: Manage the semantic model development lifecycle
Manage semantic models through their full development lifecycle. Create reusable assets, version-control with Git, inspect and validate with the XMLA endpoint and SemPy, deploy through pipelines, and maintain with monitoring and impact analysis.
Module 16: Prepare the semantic layer for AI in Microsoft Fabric
Design gold layers, semantic models, and documentation that enable Copilot, data agents, and enterprise ontologies to deliver accurate, business-relevant insights.
Module 17: Understand Microsoft Fabric IQ fundamentals
Microsoft Fabric IQ provides a way to define business vocabulary in an ontology and bind the ontology to data sources. Learn about ontology items, data agents, Graph in Microsoft Fabric, and Power BI semantic models. Discover how ontology modeling differs from traditional analytical modeling by starting with business concepts rather than specific use cases.
Module 18: Create an ontology with Fabric IQ
Ontologies in Fabric IQ transform your data into a business vocabulary that everyone can understand. In this module, you'll learn two ways to create ontologies - building manually to understand the core components, or generating automatically from Power BI semantic models to accelerate development. You'll practice both approaches and learn how to connect your ontology to data sources in OneLake, including lakehouse tables and eventhouse streams.
Module 19: Secure data access in Microsoft Fabric
Microsoft Fabric uses a multi-layer security model with access controls at different levels.
Module 20: Secure a Microsoft Fabric data warehouse
Data warehouse in Microsoft Fabric is a comprehensive platform for data and analytics, featuring advanced query processing and full transactional T-SQL capabilities for easy data management and analysis.
Module 21: Govern data in Microsoft Fabric with Purview
Learn how Microsoft Purview enables the comprehensive data governance for your Microsoft Fabric data lakes. Ensure that data is both tightly controlled and highly available for compliant analysis.
Module 22: Govern analytics data in Microsoft Fabric
Implement Fabric-native governance practices including data classification, sensitivity labels, endorsement, and documentation. Ensure data assets are trustworthy and governed for both human and AI consumption.