Fundamentals of Data Analytics

Faculty
Commerce & Business Administration
Department
Computing Studies & Information Systems
Course Code
CSIS 3360
Credits
3.00
Semester Length
15 Weeks
Max Class Size
35
Method Of Instruction
Lecture
Seminar
Typically Offered
To be determined
Campus
Online

Overview

Course Description
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
   
Assignments/Project:    10% - 25%
Quizzes (Minimum 2)  10% - 20%
Midterm exam  20% - 30%
Final Exam * 30% - 40%
Total 100%

Some of the assessments may involve group work.

* Practical hands-on computer exam

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

At the end of this course, the successful student will be able to:

  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.
Textbook Materials

No Text Required, Notes to be provided by Instructor

References:         

EMC Education Services.  Data Science & Big Data Analytics - Latest Ed., Wiley

Tableau documentation / guides.

Requisites

Prerequisites

min grade of C in 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

No corequisite courses.

Equivalencies

No equivalent courses.

Requisite for

This course is not required for any other course.

Course 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 Transfers

Institution Transfer Details Effective Dates
Athabasca University (AU) AU COMP 3XX (3) 2017/01/01 to -
Coquitlam College (COQU) No credit 2015/01/01 to -
Kwantlen Polytechnic University (KPU) No credit 2015/01/01 to -
Langara College (LANG) LANG STAT 2XXX (3) 2015/01/01 to -
Northern Lights College (NLC) No credit 2018/01/01 to -
Okanagan College (OC) OC COSC 2XX (3) 2016/09/01 to -
Simon Fraser University (SFU) SFU STAT 2XX (3) 2015/01/01 to -
University Canada West (UCW) UCW CPSC 2XX (3) 2015/01/01 to -
University of Northern BC (UNBC) UNBC CPSC 2XX (3) 2015/01/01 to -
University of the Fraser Valley (UFV) UFV COMP 3XX (3) 2015/01/01 to -
University of Victoria (UVIC) UVIC CSC 2XX (1.5) 2015/01/01 to -

Course Offerings

Fall 2020

CRN
Days
Dates
Start Date
End Date
Instructor
Status
Location
35587
Wed
08-Sep-2020
- 07-Dec-2020
08-Sep-2020
07-Dec-2020
Bhardwaj
Nikhil
Waitlist
Online
This course will include synchronous on-line activities. Students should plan to be available on-line at scheduled course times.
Max
Enrolled
Remaining
Waitlist
35
35
0
5
Days
Building
Room
Time
Wed
9:30 - 12:20