vcc.ca
ITPM 3210: Data Analytics in IT Project Environments
Effective date
January 2026
Department
IT Project Management
School
Hospitality, Food Studies and Applied Business
Description
This course delves into the principles and advanced techniques of business data analysis and effective data visualization within the realm of Information Technology. Students will engage with real-world IT data to uncover patterns, trends, and relationships, driving strategic decision-making in technology-driven environments. Key components include data exploration, dimensional analysis, hypothesis formulation, and the creation of compelling visual presentations using state-of-the-art IT tools. Through a collaborative group project, students will tackle real-world IT data analysis challenges, transforming raw data into strategic insights and effectively communicating these findings to stakeholders. The course emphasizes the use of IT-specific software and platforms, ensuring students are well-versed in the latest technologies and methodologies in the field of IT Business Analytics.
Credits
3.0
Year of study
3rd Year Post-secondary
Prerequisites
None
Corequisites
None
Course Learning Outcomes
Upon successful completion of this course, students will be able to:
- Explain the value of data analytics and visualization for business organizations and/or in an IT context.
- Describe contemporary approach to Business Intelligence / Data Analytics.
- Analyze Business Intelligence Trends & Trends in Big Data.
- Perform advanced analysis by joining and blending data from different sources.
- Apply advanced analytical techniques and IT tools to effectively analyze and interpret business data, driving strategic decision-making and innovation.
- Formulate and implement data analytics strategies using cutting-edge IT tools to solve business problems and enhance organizational performance.
- Perform basic programming in data analytics (e.g. Python etc.).
Prior Learning Assessment & Recognition (PLAR)
None
Hours
Lecture, Online, Seminar, Tutorial: 45
Total Hours: 45
Total Hours: 45
Instructional Strategies
Class-Based: This course will be presented using a variety of instructional strategies, resources and activities including lectures, active learning strategies, online activities, group activities, and projects.
Online/Asynchronous: Videos, discussion forums, teamwork, case studies, presentations.
Online/Asynchronous: Videos, discussion forums, teamwork, case studies, presentations.
Grading System
Letter Grade (A-F)
Passing grade
D
Evaluation Plan
|
Type |
Percentage |
Assessment activity |
|
Assignments |
60 |
Class-Based. Six assignments at 10% each |
|
Quizzes/Tests |
10 |
Class-Based. |
|
Midterm Exam |
10 |
Class-Based. |
|
Final Exam |
20 |
Class-Based. |
|
Quizzes/Tests |
10 |
Online. A number of open book quizzes. |
|
Assignments |
40 |
Online. Four or more assignments connected to data visualization or dataset analysis. |
|
Assignments |
20 |
Online. Final reflection paper. |
|
Project |
30 |
Online. Includes components such as written report, peer evaluation, and presentation. |
Course topics
- Introduction to Big Data Analytics Data Analytics Lifecycle Data Mining Process Review Basic Data Analytics Methods and planning data analytic steps Advanced Analytics – Technology and Tools Decision Analysis through designing visualizations Present data using story points and fully interactive dashboards Perform advanced analysis by joining and blending data from different sources Introduction to Programming in Data Analytics
Notes:
- Course contents and descriptions, offerings and schedules are subject to change without notice.
- Students are required to follow all College policies including ones that govern their educational experience at VCC. Policies are available on the VCC website at:
https://www.vcc.ca/about/governance--policies/policies/. - To find out if there are existing transfer agreements for this course, visit the BC Transfer Guide at https://www.bctransferguide.ca.