Douglas College wordmark
Facebook logo Twitter logo Instagram logo Snapchat logo YouTube logo Wordpress logo

Registration for the Fall 2019 semester begins June 25.  Watch your email for more details.

back to search

Fundamentals of Data Analytics

Course Code: CSIS 3360
Faculty: Commerce & Business Administration
Credits: 3.0
Semester: 15
Learning Format: Lecture, Seminar
Typically Offered: TBD. Contact Department Chair for more info.
course overview

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.

Course Content

  1. Introduction to Big Data Analytics
  2. Data Analytics Lifecycle
  3. Data Mining Process
  4. Review Basic Data Analytics Methods and planning data analytic steps
  5. Business Intelligence Trends and Big Data Trends
  6. Make use of MS Excel pivot tables for analytics
  7. Exploring the use of one of the data analytics tools – Tableau among many out there
  8. Advanced Analytics – Technology and Tools
  9. Database Analytics using Tableau
  10. Decision Analysis through designing visualizations

Methods of Instruction

Lecture, seminar and hands-on exercises in the lab

Means of Assessment

Participation 0% - 5%
Assignments/Project:    15% - 25%
Quizzes (Minimum 2) * 10% - 20%
Midterm exam * 20% - 30%
Final Exam * 25% - 35%
Total 100%

# 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).

Learning Outcomes

  1. Explain foundations of Big Data Analytics & Data Mining Process
  2. Describe modern approach to Business Intelligence / Data Analytics
  3. Analyse Business Intelligence Trends & Trends in Big Data
  4. Utilize effective ways to analyze data
  5. Develop data analytics plan
  6. Use data analytic tools such as Tableau
  7. Explore Advanced Analytics – Technology and Tools.
  8. Explain philosophies, tools and techniques of decision analysis in terms of data management and data visualization.

course prerequisites

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.

Corequisites

Courses listed here must be completed either prior to or simultaneously with this course:

  • No corequisite courses

Equivalencies

Courses listed here are equivalent to this course and cannot be taken for further credit:

  • No equivalency courses

curriculum guidelines

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.

course schedule and availability
course transferability

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.

assessments

If your course prerequisites indicate that you need an assessment, please see our Assessment page for more information.

noticecurriculum notice

There is an upcoming curriculum change scheduled for .
View upcoming changes