“The Microsoft Fabric implementation program gave our data engineering team a structured path from legacy pipelines to a modern lakehouse architecture.”
Microsoft Official Curriculum
Role-Based Certification PrepTrack: Microsoft Certified: Fabric Analytics Engineer AssociateOfficial Source: Microsoft Learn
MicrosoftAdvanced
Implement analytics solutions using Microsoft Fabric
This course covers how to prepare, enrich, and serve data for analysis by consumers such as data analysts, report developers, and AI agents. The course focuses on designing dimensional models and transforming data by using dataflows, notebooks, and T-SQL across lakehouses, warehouses, and eventhouses in Microsoft Fabric. The course also covers building and optimizing semantic models, managing the analytics development lifecycle, and enforcing security and governance across data assets.
Duration
4 days
Level
Intermediate
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
Enterprise Track
Microsoft
Data AnalyticsMF
Fabric Analytics Engineer Associate
Fabric
FAB
On this page
Ideal for
Data AnalystData AnalyticsCertification ReadinessTailored Team Delivery
Audience Profile
Built for these roles
This course is intended for data professionals with experience in data modeling, transformation, and analytics. Learners should have prior experience translating business requirements into analytical measures by using Structured Query Language (SQL) or Data Analysis Expressions (DAX). Experience building semantic models and reports in Power BI is recommended. Familiarity with Kusto Query Language (KQL) and Python is also helpful but not required.
Overview
Executive overview
As a candidate for this certification, you should have subject matter expertise in designing, creating, and managing analytical assets, such as semantic models, warehouses, or lakehouses.
Program Outcomes
Capabilities your teams will gain
Maintain a data analytics solution
Prepare data
Implement and manage semantic models
Curriculum
Curriculum roadmap
1
Maintain a data analytics solution
2
Prepare data
3
Implement and manage semantic models
1Module 1
Explore analytics data stores in Microsoft Fabric
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Module 1
Explore analytics data stores in Microsoft Fabric
Understand how Microsoft Fabric unifies analytics storage through OneLake, and evaluate when to use lakehouses, warehouses, or eventhouses for your data workloads.
- Introduction to end-to-end analytics using Microsoft Fabric
- Discover and connect to data in OneLake
- Get started with lakehouses in Microsoft Fabric
- Get started with data warehouses in Microsoft Fabric
- Get started with Real-Time Intelligence in Microsoft Fabric
2Module 2
Design and transform analytics data in Microsoft Fabric
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Module 2
Design and transform analytics data in Microsoft Fabric
Design dimensional models and apply transformations using dataflows, Spark notebooks, and T-SQL to produce consistent, analysis-ready data in Microsoft Fabric.
- Choose data stores in Microsoft Fabric
- Design dimensional models for analytics in Microsoft Fabric
- Transform data using Dataflows Gen2 in Microsoft Fabric
- Transform data using notebooks in Microsoft Fabric
- Transform data using T-SQL in Microsoft Fabric
3Module 3
Design and manage semantic models in Microsoft Fabric
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Module 3
Design and manage semantic models in Microsoft Fabric
Create semantic models that serve reliable, governed analytics at scale — from initial DAX logic through performance optimization, data access control, and automated lifecycle management.
- Create DAX calculations in semantic models
- Design semantic models for scale in Microsoft Fabric
- Optimize semantic model performance
- Enforce semantic model security
- Manage the semantic model development lifecycle
4Module 4
Prepare AI-ready analytics data in Microsoft Fabric
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Module 4
Prepare AI-ready analytics data in Microsoft Fabric
Prepare your semantic layer for AI by adding metadata and linguistic context to gold-layer data stores and semantic models, then generate ontologies that AI agents use to answer business questions.
- Prepare the semantic layer for AI in Microsoft Fabric
- Understand Microsoft Fabric IQ fundamentals
- Create an ontology with Fabric IQ
5Module 5
Secure and govern analytics data in Microsoft Fabric
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Module 5
Secure and govern analytics data in Microsoft Fabric
Implement layered access controls across Microsoft Fabric workspaces and data stores, then establish governance policies that help consumers identify trustworthy, certified analytics assets.
- Secure data access in Microsoft Fabric
- Secure a Microsoft Fabric data warehouse
- Govern analytics data in Microsoft Fabric
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
Certification readinessImplementation-focused labsPrivate cohort deliveryIntermediate practitioner depth
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Builds current Microsoft credential readiness for Fabric Analytics Engineer Associate using the official Microsoft Learn skill outline.
- •Align labs to your Microsoft tenant and workload scenarios
- •Add readiness checks and exam preparation reviews
- •Extend delivery with role-specific implementation workshops
Credentials
Certification & official source
- •Microsoft Certified: Fabric Analytics Engineer Associate
Aligned to the official Microsoft Learn course and learning path for this program.
View Official Microsoft Learn PageResources
Program resources
Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.
Enterprise Proof
Trusted delivery outcomes
Delivery Capability
Enterprise-grade instruction
MCT-led delivery
Programs led by Microsoft Certified Trainer practitioners
Enterprise program oversight
Founder-led specialist delivery with structured rollout planning
Global delivery
APAC · EMEA · Americas · Virtual & Onsite
Implementation-focused
Hands-on labs aligned to production scenarios
