Course

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(s) Of Instruction
Lecture
Seminar
Typically Offered
To be determined

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
Learning Activities

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).

Students may conduct research as part of their coursework in this class. Instructors for the course are responsible for ensuring that student research projects comply with College policies on ethical conduct for research involving humans, which can require obtaining Informed Consent from participants and getting the approval of the Douglas College Research Ethics Board prior to conducting the research.

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

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

  • No equivalency courses

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.

(Current)

Course Transfers

These are for current course guidelines only. For a full list of archived courses please see https://www.bctransferguide.ca

Institution Transfer Details for CSIS 3360
Athabasca University (AU) AU COMP 3XX (3)
Coquitlam College (COQU) No credit
Kwantlen Polytechnic University (KPU) No credit
Langara College (LANG) LANG STAT 2XXX (3)
Northern Lights College (NLC) No credit
Okanagan College (OC) OC COSC 2XX (3)
Simon Fraser University (SFU) SFU STAT 2XX (3)
University Canada West (UCW) UCW CPSC 2XX (3)
University of Northern BC (UNBC) UNBC CPSC 2XX (3)
University of the Fraser Valley (UFV) UFV COMP 3XX (3)
University of Victoria (UVIC) UVIC CSC 2XX (1.5)

Course Offerings

Fall 2024

CRN Days Instructor Status
CRN
35587
 Wed
Instructor Last Name
Bhardwaj
Instructor First Name
Nikhil
Course Status
Open
Maximum Seats
35
Currently Enrolled
0
Remaining Seats:
35
On Waitlist
0
Building
New Westminster - North Bldg.
Room
N6107
Times:
Start Time
9:30
-
End Time
12:20
Section Notes

CSIS 3360 001 - This section is restricted to PDD Data Analytics, PBD Data Analytics Stream, and PBD Health Info Management students.

CRN Days Instructor Status
CRN
35733
 Thu
Instructor Last Name
Bhardwaj
Instructor First Name
Nikhil
Course Status
Open
Maximum Seats
35
Currently Enrolled
1
Remaining Seats:
34
On Waitlist
0
Building
New Westminster - North Bldg.
Room
N6107
Times:
Start Time
9:30
-
End Time
12:20
Section Notes

CSIS 3360 002 - This section is restricted to PDD Data Analytics, PBD Data Analytics Stream, and PBD Health Info Management students.

CRN Days Instructor Status
CRN
37761
 Mon
Instructor Last Name
TBA
Instructor First Name
(Faculty)
Course Status
Open
Maximum Seats
35
Currently Enrolled
0
Remaining Seats:
35
On Waitlist
0
Building
New Westminster - North Bldg.
Room
N6109
Times:
Start Time
15:30
-
End Time
18:20
Section Notes

CSIS 3360 003 - This section is restricted to PDD Data Analytics, PBD Data Analytics Stream, and PBD Health Info Management students.