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Course Description

Learn the comprehensive capabilities of Microsoft Fabric in this course designed for IT professionals and data analysts. Microsoft Fabric is a cutting-edge end-to-end analytics and data platform tailored for enterprise-level integration and efficiency. This course dives deep into Fabric's unified solution approach, covering essential components such as data movement, processing, ingestion, transformation, real-time event routing, and report generation.

You will gain hands-on experience with Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models, to create and deploy analytics assets. This course is best suited for those who have completed DAT 350 Microsoft Power BI Data Analyst, or similar expertise in using Power BI for data transformation, modeling, visualization, and sharing.

This course covers the objectives for Microsoft Exam DP-600: Microsoft Fabric Analytics Engineer.

The University of Calgary is a Microsoft Education Global Training Partner.

Course Details

Learning Outcomes

By the completion of this course, students will be able to:

  • Plan, implement, and manage a solution for data analytics with Microsoft Fabric
  • Prepare and serve data in a lakehouse or warehouse
  • Implement and manage semantic models in Microsoft Fabric
  • Explore and analyze data 

Topics

  • Implement a Lakehouse with Microsoft Fabric
    • Use Apache Spark 
    • Work with Delta Lake tables 
    • Use Data Factory pipelines 
    • Organize a Fabric lakehouse using medallion architecture design
  • Ingest data with Microsoft Fabric
    • Ingest Data with Dataflows Gen2 in Microsoft Fabric
    • Ingest Data with Spark and Microsoft Fabric notebooks
    • Use Data Factory pipelines in Microsoft Fabric
  • Implement a data warehouse with Microsoft Fabric
    • Load data into a Microsoft Fabric data warehouse
    • Query a data warehouse in Microsoft Fabric
    • Monitor a Microsoft Fabric data warehouse
    • Secure a Microsoft Fabric data warehouse
  • Work with semantic models in Microsoft Fabric
    • Understand Scalability in Power BI
    • Create Power BI model relationships
    • Use tools to optimize Power BI Performance
    • Enforce Power BI model security

Notes

This course includes hands-on activities to reinforce the concepts taught and provide a practical learning experience.

Lab access will be provided at no additional cost.

Prerequisites

No mandatory pre-requisite. 

Self-assessment for enrolment: 

A minimum of 6 months relevant working experience and knowledge in: 

  • Using Power BI for data transformation, modeling, visualization, and sharing
  • Building and deploying data analytics solutions at the enterprise level

OR

Recommended prerequisites: 

  • ICT-902/ICT-906 Microsoft Azure Data Fundamentals   
  • DAT 350 Microsoft Power BI Data Analyst 

Applies Towards the Following Program(s)

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Type
Online Synchronous
Days
M, W
Time
6:00PM to 9:00PM
Dates
Feb 24, 2025 to Mar 26, 2025
Schedule and Location
Hours
30.0
Delivery Options
Course Fees
Flat fee non-credit $979.00
Instructor(s)
  • Ashraf Ghonaim
Reading List / Textbook
No Textbook Required.
Section Notes

Classes are held online in real time (Mountain Time) at the specified time and dates.

This course uses:

  • Desire2Learn (D2L), an online learning management system. The instructor will post the course outline and other materials in D2L.
  • Zoom web conferencing software.

To fully participate in the live sessions, students will need: an internet connection, and a reliable headset with microphone.

For more information, please visit our Online Learning Resources.

Unless notified, all online courses are available at 9 am MT the day before the start date. Students registering on (or after) the start date will receive access within one day of registration.

Students unfamiliar with online learning are encouraged to take our free Digital Skills for Learning Online course.

Unless otherwise stated, notice of withdrawal or transfer from a course must be received at least seven calendar days prior to the start date of the course.

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