Course

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(s) of instruction
Online
Hybrid
Lecture
Seminar
Course designation
Certificate in Global Competency
Industry designation
CPA,PEP
Typically offered
To be determined

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
Learning activities

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%

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

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 with a minimum grade of C) and (CSIS 1190 or CSIS 2200 with a minimum grade of C)

Or currently active in one of the following:

PDD Accounting
PDD Data Analytics

Or (ACCT 1210 OR ACCT 1235 with a minimum grade of C) and currently active in one of the following:

PBD Acct & Finance
PDD Accounting Studies

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

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

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

Institution Transfer details for ACCT 3880
Athabasca University (AU) AU ACCT 2XX (3)
Capilano University (CAPU) CAPU BADM 2XX (3)
Coast Mountain College (CMTN) CMTN BADM 2XX (3)
College of the Rockies (COTR) COTR ACCT 2XX (3)
Kwantlen Polytechnic University (KPU) No credit
Simon Fraser University (SFU) No credit
University Canada West (UCW) No credit
University of Northern BC (UNBC) No credit
University of the Fraser Valley (UFV) UFV BUS 3XX (3)
University of Victoria (UVIC) UVIC COM 3XX (1.5)
Vancouver Island University (VIU) VIU ACCT 3rd (3)

Course Offerings

Winter 2025

CRN
15278
section details
CRN Days Instructor Status More details
Maximum seats
35
Currently enrolled
35
Remaining seats:
0
On waitlist
0
Building
New Westminster - North Bldg.
Room
N6105
Times:
Start Time
15:30
-
End Time
18:20
Section notes

This is a hybrid synchronous course that incorporates both face-to-face and online instructions at scheduled times. Classes will meet in person: TBA

CRN
15517
section details
CRN Days Instructor Status More details
Maximum seats
35
Currently enrolled
34
Remaining seats:
1
On waitlist
7
Building
Online
Room
ONLINE
Times:
Start Time
18:30
-
End Time
21:20
Section notes

This course will include synchronous online activities. Students should plan to be available online at scheduled course times.