In this course, students will gain the basic understanding of the emerging Data Analytics field. The students will be required to work with real-world examples using current computing tools. Integral to the course is a group project where students will complete a variety of tasks including: requirement elicitation; developing hypothesis; data exploration; dimensional analysis; identifying metrics; and visual presentation of results.
- Introduction to Big Data Analytics
- Data Analytics Lifecycle
- Data Mining Process
- Review Basic Data Analytics Methods and planning data analytic steps
- Business Intelligence Trends and Big Data Trends
- Make use of MS Excel pivot tables for analytics
- Exploring the use of one of the data analytics tools – Tableau among many out there
- Advanced Analytics – Technology and Tools
- Database Analytics using Tableau
- Decision Analysis through designing visualizations
Methods of Instruction
Lecture, seminar and hands-on exercises in the lab
Means of Assessment
||0% - 5%
||15% - 25%
|Quizzes (Minimum 2) *
||10% - 20%
|Midterm exam *
||20% - 30%
|Final Exam *
||25% - 35%
# Some of the assessments may involve group work.
*In order to pass the course, students must, in addition to receiving an overall course grade of 50%, also achieve a grade of at least 50% on the combined weighted examination components (including quizzes, tests, exams).
- Explain foundations of Big Data Analytics & Data Mining Process
- Describe modern approach to Business Intelligence / Data Analytics
- Analyse Business Intelligence Trends & Trends in Big Data
- Utilize effective ways to analyze data
- Develop data analytics plan
- Use data analytic tools such as Tableau
- Explore Advanced Analytics – Technology and Tools.
- Explain philosophies, tools and techniques of decision analysis in terms of data management and data visualization.
CSIS 2200 AND (BUSN 2429 or MATH 1160)
(Note: CSIS 2300 is recommended)
Students are expected to be comfortable using MS Excel. For those needing upgrading, CSIS 1190 is recommended.
Courses listed here must be completed either prior to or simultaneously with this course:
Courses listed here are equivalent to this course and cannot be taken for further credit:
Course Guidelines for previous years are viewable by selecting the version desired. If you took this course and do not see a listing for the starting semester/year of the course, consider the previous version as the applicable version.
Below shows how this course and its credits transfer within the BC transfer system.
A course is considered university-transferable (UT) if it transfers to at least one of the five research universities in British Columbia: University of British Columbia; University of British Columbia-Okanagan; Simon Fraser University; University of Victoria; and the University of Northern British Columbia.
For more information on transfer visit the BC Transfer Guide and BCCAT websites.
If your course prerequisites indicate that you need an assessment, please see our Assessment page for more information.