Microsoft Fabric Analytics Engineer

Introduction to end-to-end analytics using Microsoft Fabric

Discover how Microsoft Fabric can meet your enterprise's analytics needs in one platform. Discover the capabilities Fabric has to offer, understand how it works, and identify how you can use Fabric for your analytics needs.

• 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

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.

• Understand OneLake
• Browse and connect to data in OneLake
• Discover streaming data in Real-Time hub
• Exercise - Discover and connect to data in OneLake

Get started with lakehouses in Microsoft Fabric

Lakehouses in Microsoft Fabric combine data lake flexibility with data warehouse analytics. Learn how to create, load, and query a lakehouse on a single platform.

• Describe lakehouse features and capabilities
• Ingest and transform data in a lakehouse
• Query and analyze lakehouse data
• Exercise - Create a Microsoft Fabric lakehouse
• Module assessment

Get started with data warehouses in Microsoft Fabric

Understand the key components and design considerations for implementation of 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
• Exercise - Create and query a warehouse
• Module assessment

Get started with Real-Time Intelligence in Microsoft Fabric

Real-Time Intelligence in Microsoft Fabric has capabilities that help you ingest, process, store, visualize, and act on data in motion to gain immediate insights from events as they happen.

• 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
• Exercise - Get started with Real-Time Intelligence in Microsoft Fabric
• Module assessment

Choose data stores in Microsoft Fabric

Evaluate lakehouse, warehouse, and eventhouse options in Microsoft Fabric to select the appropriate analytical data store for different business scenarios based on data format, query language, write patterns, and team skills.

• 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

Learn dimensional schema types, fact and dimension table design, and slowly changing dimension patterns for analytics workloads in Microsoft Fabric.

• Describe dimensional schema types
• Design fact tables
• Design dimension tables
• Implement slowly changing dimensions
• Exercise: Design and implement a dimensional model

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.

• Understand Dataflows Gen2
• Transform data with Power Query
• Optimize Dataflows Gen2 performance
• Exercise: Transform data with Dataflows Gen2

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.

• Describe notebooks in Fabric
• Shape and clean data
• Combine and aggregate data
• Write and size Delta tables
• Exercise: Transform data with notebooks

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.

• Transform data with T-SQL queries
• Create views for reusable logic
• Build stored procedures
• Implement dimensional tables
• Exercise: Transform data with T-SQL

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.

• Create calculated tables
• Create calculated columns
• Understand implicit measures
• Create explicit measures
• Use iterator functions
• Exercise - Create DAX calculations
• Check your knowledge

Design semantic models for scale in Microsoft Fabric

Design semantic models for scale in Microsoft Fabric. Choose storage modes, design star schema relationships, create scalable calculation patterns, and configure settings for large datasets and concurrent consumption.

• Choose a storage mode
• Design star schema for semantic models
• Design scalable calculations
• Configure settings for scale
• Exercise: Design a semantic model for scale in Fabric
• Module assessment

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.

• Use Performance analyzer to diagnose issues
• Optimize DAX calculations
• Reduce cardinality for better performance
• Implement aggregations
• Troubleshoot common performance issues
• Exercise: Diagnose and fix a slow report

Enforce semantic model security

Implement row-level security, object-level security, and dynamic security patterns to protect sensitive data in semantic models.

• Implement row-level security
• Apply object-level security
• Test security and manage roles
• Exercise: Implement RLS for a semantic model
• Module assessment

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.

• 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
• Exercise: Manage semantic models through their lifecycle
• Module assessment

Prepare semantic models for AI in Power BI and Microsoft Fabric

Design gold layers, semantic models, and documentation that enable Copilot, data agents, and enterprise ontologies to deliver accurate, business-relevant insights.

• Explain how semantic model context guides Copilot answers
• Design a focused gold layer for AI consumption
• Select the appropriate prep for AI control
• Decide when to extend a semantic model with Fabric IQ
• Validate AI readiness
• Exercise: Prepare a semantic model for AI
• Module assessment

Understand Microsoft Fabric IQ fundamentals

Learn the fundamentals of Microsoft Fabric IQ, including how ontologies create a shared business vocabulary, the six items in the IQ workload, and how ontology modeling differs from traditional data modeling approaches.

• Get started with Fabric IQ
• Explore Microsoft Fabric IQ components
• Understand the ontology modeling paradigm
• Module assessment

Create an ontology with Fabric IQ

Learn how to create ontologies in Fabric IQ by building manually or generating from Power BI semantic models, then bind ontology definitions to OneLake data sources including lakehouse tables and eventhouse streams.

• 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
• Exercise - Build an ontology manually
• Exercise - Generate an ontology from a Power BI semantic model
• Module assessment

Secure data access in Microsoft Fabric

Implement workspace roles, item permissions, and OneLake security roles to control data access in Microsoft Fabric.

• Understand the Fabric security model
• Configure workspace and item permissions
• Apply granular permissions
• Exercise: Secure data access in Microsoft Fabric
• Module assessment

Secure a Microsoft Fabric data warehouse

Learn the key concepts and strategies for protecting sensitive data in Microsoft Fabric data warehouses.

• 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
• Module assessment

Govern analytics data in Microsoft Fabric

Apply governance controls in Microsoft Fabric to classify sensitive data, signal trust with endorsement, and monitor governance posture using the OneLake catalog.

• Classify and protect data in Microsoft Fabric
• Endorse and document data assets
• Monitor and manage governance
• Exercise - Govern analytics data in Microsoft Fabric