Following on from COMP 2156 , and parallel to COMP 3157, this hands-on advanced course was designed for Business Intelligence and Data Analysts. Students who already know how to use Power BI to build and publish reports begin with an in-depth introduction to Star Schema and its relevance to optimal Power BI data modeling. COMP 3156 in-class labs and exercises focus on specific strategies to optimize large complex Power BI data models and how to leverage Power BI Service in the cloud for fast performing reports. Topics include relational data modeling in Power BI, Designing Import, DirectQuery, and Composite Data Models. There is also an in-depth explanation of Power BI Service Performance Monitoring. Tabular Editor and DAX Studio are also discussed. Labs and assignments include managing security permissions, data visibility based on role as and leveraging specialized third-party tools. Tabular Editor and DAX Studio are used to monitor and evaluate data model performance. Participants must provide their own current model PC capable of running Windows 10 and MS Excel, with an i5 or higher equivalent processor, 8 GB minimum RAM, and 256 GB minimum storage. High-speed internet access is needed for online sections and for homework. COMP 3156 is an elective in several BCIT Computing credentials including the CST Diploma (FLEX), and the Applied Data Analytics Certificate (ADAC). By the end of this course, successful students will be able to build advanced, optimized data models and use the Power BI Service cloud environment.
- 60% in COMP 2156
Below is one offering of COMP 3156 for the Spring/Summer 2023 term.
Wed Apr 12 - Wed May 17 (6 weeks)
- 6 weeks
- CRN 68721
Class meeting times
|Apr 12 - May 17||Wed||18:30 - 21:30||Online|
Course outline TBD — see Learning Outcomes in the interim.
- Internet delivery format.
- Departmental approval needed
- Important course information will be sent to you prior to your course start date. Check your myBCIT email account to access this information.
Please email email@example.com for Departmental approval. Include your Student number (A0#) and COMP__ and preferred CRN __ and Program Declaration____. Course is 18 hours synchronous online classes. Late registration is not permitted.
This course offering is full. Please check back next term, subscribe to receive email updates or contact us with your comments or questions.
Upon successful completion of this course, the student will be able to:
- Describe Star Schema and its relevance to developing optimized Power BI data models.
- Implement various techniques to reduce data model size and improve model performance.
- Describe the implications of import, direct-query and composite data models.
- Diagnose and troubleshoot common data relationship issues with your Power BI data model.
- Conduct performance testing to identify opportunities for optimization.
- Manage Row-Level Security (Dynamic & Static).
- Describe the data architecture of Power BI Service.
- Monitor a Power BI environment as a Power BI administrator for a Power BI Service in the cloud.
Effective as of Fall 2022
MS Power BI Optimization (COMP 3156) is offered as a part of the following programs:
School of Computing and Academic Studies
- Applied Computer Information Systems (ACIS)
Associate Certificate Part-time
- Applied Data Analytics
- Applied Database Administration and Design
Associate Certificate Part-time
- Computer Systems
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