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Express: Microsoft Fabric Analytics Course

Class Dates
(click date for class times)
(click Enroll for locations)
9/10-9/11
Class Dates and Times
09/10/2026Thursday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
09/11/2026Friday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
Last Reg Date9/4
 
Fee:  $995

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Express: Microsoft Fabric Analytics Course

 

Special Note to New Hampshire Residents
This course has not yet been approved by the New Hampshire Department of Education. Please contact us for an update on when the class will be available in New Hampshire.

Overview

Prepare data that BI users, Copilot experiences, and AI agents can trust. This Express course helps analytics engineers, BI developers, Power BI modelers, and data analysts use Microsoft Fabric to discover, transform, model, secure, and manage reusable analytics assets that support reporting and downstream AI experiences.
A DP-600-based but differentiated analytics course focused on governed, AI-ready data, semantic models for Copilot and agents, reusable semantic data products, lifecycle, and the Power BI and PL-300 bridge.

Who should attend

Analytics engineers, BI developers, Power BI modelers, data analysts, data platform owners, and AI-ready data owners.

Prerequisites

Power BI, SQL, data modeling, or analytics experience recommended. Fabric familiarity helpful but not required.
Recommended prior course or experience: PL-300, Power BI modeling, SQL analytics experience, or data fundamentals. AI Briefings / Skill Sprints for business context.

Course Outline

Fabric analytics landscape

  • Fabric map: OneLake, lakehouse, warehouse
  • Analytics engineer vs analyst and engineer roles
  • AI-ready data and semantic context for agents
  • Portfolio connection to Copilot experiences

Getting and organizing data

  • Data connections and source planning
  • OneLake catalog and Real-Time hub discovery
  • Ingestion vs shortcut vs mirrored data
  • Intake checklist: owner, sensitivity, lineage

Transforming and enriching data

  • Dataflows Gen2, notebooks, T-SQL, and KQL
  • Cleansing, merging, aggregation, enrichment
  • Data quality checks before modeling
  • Low-code vs code-based transformation

Designing analytical stores

  • Lakehouse, warehouse, and eventhouse patterns
  • Star schema design for lakehouse or warehouse
  • Grain, facts, dimensions, and relationships
  • Store decision matrix by workload and skill

Querying and analyzing data

  • SQL, KQL, DAX, and visual query editor roles
  • Reusable query patterns for validation
  • KQL for eventhouse and real-time analytics
  • DAX bridge into semantic model measures

Semantic models for BI, Copilot, and agents

  • Semantic model as reusable business logic
  • Import, DirectQuery, Direct Lake, composite
  • Relationships, measures, and calc groups
  • Semantic assets that support Copilot answers

Power BI and PL-300 bridge

  • Report and model expectations for Power BI
  • When Fabric Express is enough vs PL-300
  • Reusable semantic products for authors
  • Adoption and governance implications

Security, governance, and sensitivity

  • Workspace roles, permissions, and lineage
  • Sensitivity labels and compliance controls
  • Least-privilege access for AI consumers
  • Governed data exposure for Copilot and agents

Analytics lifecycle and deployment

  • Git integration and deployment pipelines
  • Versioning, impact analysis, and notes
  • Reusable assets and ownership model
  • Lifecycle checklist for semantic products

AI-ready analytics capstone

  • Design a Fabric data and semantic layer
  • Identify stores, model, governance, lifecycle
  • Document downstream AI-readiness assumptions

 

View outline in Word

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Attend hands-on, instructor-led Express: Microsoft Fabric Analytics training classes at ONLC's nationwide locations. Not near one of our locations? Attend these same live classes from your home/office PC via our Remote Classroom Instruction (RCI) technology.

For additional training options, check out our list of Courses and select the one that's right for you.

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