Implement analytics solutions using Microsoft Fabric (DP-600T00)
Learn to build secure, governed analytics solutions in Microsoft Fabric using lakehouses, warehouses, dataflows, notebooks, T-SQL, DAX, and semantic models.
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Course Overview
Learn how to prepare, enrich, and serve data for analytics with Microsoft Fabric. This course covers dimensional modeling and data transformation with Dataflows Gen2, notebooks, and T-SQL across lakehouses, warehouses, and eventhouses. You will also explore scalable semantic models, DAX calculations, lifecycle management, AI readiness, security, and data governance.
This course is intended for experienced data professionals who translate business requirements into analytical models and measures.
Course Benefits
- Build end-to-end analytics solutions with Microsoft Fabric and OneLake.
- Evaluate and use lakehouses, warehouses, and eventhouses for analytical workloads.
- Design dimensional models with fact tables, dimension tables, and slowly changing dimensions.
- Transform data with Dataflows Gen2, Power Query, notebooks, and T-SQL.
- Create DAX calculations and design scalable semantic models.
- Diagnose and improve semantic model performance.
- Secure semantic models, Fabric workspaces, data assets, and data warehouses.
- Manage semantic models through version control, deployment stages, and the XMLA endpoint.
- Prepare semantic layers for AI and create ontologies with Fabric IQ.
- Classify, protect, document, and govern analytics data with Microsoft Fabric and Microsoft Purview.
Delivery Methods
Live expert-led online training from anywhere. Guaranteed to run .
Delivered for your team at your site or online.
Microsoft Certified Partner
Webucator is a Microsoft Certified Partner. This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).

Course Outline
- Introduction to end-to-end analytics using Microsoft Fabric
- Explore end-to-end analytics with Microsoft Fabric
- Explore data teams and Microsoft Fabric
- Enable and use Microsoft Fabric
- Module assessment
- Discover and connect to data in OneLake
- Understand OneLake
- Browse and connect to data in OneLake
- Discover streaming data in Real-Time hub
- Get started with lakehouses in Microsoft Fabric
- Describe lakehouse features and capabilities
- Ingest and transform data in a lakehouse
- Query and analyze lakehouse data
- Module assessment
- Get started with data warehouses in Microsoft Fabric
- Understand data warehouses
- Understand data warehouses in Fabric
- Query and transform data
- Model data in a warehouse
- Secure and monitor a warehouse
- Module assessment
- Get started with Real-Time Intelligence in Microsoft Fabric
- What is real-time data analytics?
- Real-Time Intelligence in Microsoft Fabric
- Ingest and transform real-time data
- Store and query real-time data
- Visualize real-time data
- Automate actions
- Module assessment
- Choose data stores in Microsoft Fabric
- Describe analytical data store options
- Evaluate lakehouse capabilities
- Evaluate warehouse capabilities
- Evaluate eventhouse capabilities
- Case study: Choose data stores for an integrated analytics solution
- Module assessment
- Design dimensional models for analytics in Microsoft Fabric
- Describe dimensional schema types
- Design fact tables
- Design dimension tables
- Implement slowly changing dimensions
- Transform data using Dataflows Gen2 in Microsoft Fabric
- Understand Dataflows Gen2
- Transform data with Power Query
- Optimize Dataflows Gen2 performance
- Transform data using notebooks in Microsoft Fabric
- Describe notebooks in Fabric
- Shape and clean data
- Combine and aggregate data
- Write and size Delta tables
- Transform data using T-SQL in Microsoft Fabric
- Transform data with T-SQL queries
- Create views for reusable logic
- Build stored procedures
- Implement dimensional tables
- Create DAX calculations in semantic models
- Create calculated tables
- Create calculated columns
- Understand implicit measures
- Create explicit measures
- Use iterator functions
- Design semantic models for scale in Microsoft Fabric
- Choose a storage mode
- Design star schema for semantic models
- Design scalable calculations
- Configure settings for scale
- Module assessment
- Optimize semantic model performance
- Use Performance Analyzer to diagnose issues
- Optimize DAX calculations
- Reduce cardinality for better performance
- Implement aggregations
- Troubleshoot common performance issues
- Enforce semantic model security
- Implement row-level security
- Apply object-level security
- Test security and manage roles
- Module assessment
- Manage the semantic model development lifecycle
- Create reusable Power BI assets
- Manage Power BI content in version control
- Manage semantic models with the XMLA endpoint
- Deploy content through stages
- Maintain and monitor semantic models
- Module assessment
- Prepare the semantic layer for AI in Microsoft Fabric
- Understand what AI needs from your data
- Design gold layers with AI in mind
- Prepare a semantic model for AI
- Move from semantic models to enterprise ontology
- Validate AI readiness
- Module assessment
- Understand Microsoft Fabric IQ fundamentals
- Get started with Fabric IQ
- Explore Microsoft Fabric IQ components
- Understand the ontology modeling paradigm
- Module assessment
- Create an ontology with Fabric IQ
- Choose an ontology creation approach
- Build an ontology manually
- Generate an ontology from a Power BI semantic model
- Connect an ontology to data
- Configure ontology relationships
- Preview the ontology
- Module assessment
- Secure data access in Microsoft Fabric
- Understand the Fabric security model
- Configure workspace and item permissions
- Apply granular permissions
- Module assessment
- 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
- Module assessment
- Govern data in Microsoft Fabric with Purview
- Govern data in Microsoft Fabric
- Understand why Microsoft Purview is used with Microsoft Fabric
- Govern data in the Microsoft Purview hub
- Module assessment
- Govern analytics data in Microsoft Fabric
- Classify and protect data in Microsoft Fabric
- Endorse and document data assets
- Govern data for AI consumption
Class Materials
Each student receives a comprehensive set of materials, including course notes and all class examples.
Class Prerequisites
Experience in the following is required for this Microsoft Fabric class:
- PL-300 certification or equivalent Power BI expertise.
- Experience translating business requirements into analytical measures using SQL or DAX.
- Familiarity with enterprise-level data modeling, transformation, and deployment.
Experience in the following would be useful for this Microsoft Fabric class:
- Familiarity with Kusto Query Language (KQL).
- Familiarity with Python.
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