Data Analytics for Managers

Faculty
Commerce & Business Administration
Department
Accounting
Course Code
ACCT 3880
Credits
3.00
Semester Length
15 Weeks
Max Class Size
35
Method Of Instruction
Lecture
Seminar
Online
Hybrid
Typically Offered
To be determined
Campus
Online

Overview

Course Description
From financial statements to operating performance, the environment we are living in is “data rich, information poor.” With the decision making pressure on accountants and managers, it is crucial to gather available data quickly and provide accurate analysis. In this course the student will learn to analyze financial statements using lesser known techniques, and to address the differences among reports generated under different accounting frameworks. Students will learn to use data analytics, identify the control weaknesses and identify patterns in the transactions that point to fraud and error will be studied. Finally, the student will learn how to analyze both financial and operational data by designing financial models and dashboards, making reasonable financial forecasts, and monitoring operational performance. In this course students will have exposure to several data analytics tools.
Course Content

1.     Use the DuPont Model and ratio analysis to analyze financial statements

  • Read financial statements properly
  • Adjust financial statements
  • Analyze financial statements
  • Communicate results

2.    Apply the Data Analytics Process

  • Identify a quesion
  • Manage data
  • Perform test plan
  • Address and refine results
  • Communicate insights
  • Track outcomes

3.     Financial Modeling

  • Design and create an interactive financial model using an appropriate data analytics tool
  • Design the layout of the model clearly and logically
  • Create clearly defined inputs and assumption sections
  • Build powerful scenarios
  • Incorporate all related schedules

4. Design and create a Dashboard using an appropriate data analytics tool

  • Evaluate existing data
  • Define and calculate Key Performance Indicators (KPI)
  • Design charts and graphs for KPI
  • Present dashboard
Methods Of Instruction

In-class lectures in a computer lab and/or on-line

Means of Assessment

Assessment will be based on course objectives and will be carried out in accordance with the Douglas College Evaluation Policy. 

Projects: A minimum of two separate group data analytics projects                    40% - 50%

              A minimum of two separate individual data analytics projects                        30%

              (a mininum of 10% should be assigned to each project,
                no project should be assigned more than 40%)   

Final Exam                                                                                                       20%-30%

To pass this course, students must obtain a minimum of 50% on invigilated assessments, with the 50% calculated on a weighted average basis.

Invigilated assessments include, in-class quizzes, in-class tests, midterm exam(s) and the final exam.

Learning Outcomes

Upon completion of this course, the successful sturdent will be able to:

  • Analyze financial statements using data analytics
  • Use information from automated data capture to form and analyze financial statements
  • Access, examine and integrate different data files
  • Analyze data patterns, identify discrepancies and extract unusual items
  • Examine financial data for existence of misrepresentations in areas such as matched or unmatched records, duplication and limit violation
  • Design and construct financial models
  • Create dashboards
  • Apply the data analytics process to communucate insights and track outcomes
Textbook Materials

Data Analytics for Accounting, Richardson, Teeter, Terrall, latest international edition

and/or

other textbook(s) and/or material approved by the department 

Requisites

Prerequisites

(ACCT 1210 OR ACCT 1235 OR ACCT 3008) and (CSIS 1190 or CSIS 2200)

Or currently active in

  • PDD Accounting
  • PDD Data Analytics

Or (ACCT 1210 OR ACCT 1235) and currently active in

  • PBD Accounting and Finance
  • PDD Accounting Studies
  • PBD Accounting

Or permission of the instructor

A minimum grade of C is required in all courses.

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 ACCT 2XX (3) 2017/01/01 to -
Capilano University (CAPU) CAPU BADM 2XX (3) 2017/01/01 to -
Coast Mountain College (CMTN) CMTN BADM 2XX (3) 2017/01/01 to -
College of the Rockies (COTR) COTR ACCT 2XX (3) 2017/01/01 to -
Kwantlen Polytechnic University (KPU) No credit 2017/01/01 to -
Simon Fraser University (SFU) No credit 2017/01/01 to -
University Canada West (UCW) No credit 2017/01/01 to -
University of Northern BC (UNBC) No credit 2017/01/01 to -
University of the Fraser Valley (UFV) UFV BUS 3XX (3) 2017/01/01 to -
University of Victoria (UVIC) UVIC COM 3XX (1.5), Cannot be used for credit in BCom program. 2017/01/01 to -

Course Offerings

Winter 2021

CRN
Days
Dates
Start Date
End Date
Instructor
Status
Location
15517
Mon
04-Jan-2021
- 12-Apr-2021
04-Jan-2021
12-Apr-2021
Zhang
Zhi
Waitlist
Online
This course will include some synchronous on-line activities. Students should plan to be available on-line at scheduled course times. Synchronous on-line activities may include lecture, or they may not. In some courses, synchronous class time may be used instead for active learning components (e.g. discussions, labs).
Max
Enrolled
Remaining
Waitlist
35
35
0
6
Days
Building
Room
Time
Mon
18:30 - 21:20