Computerized Accounting and Data Analytics

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, provide accurate analysis, and present financial information to stakeholders in a meaningful way.

This course will introduce students to the concepts and practices of computerized accounting and data analytics. This course will build on and apply previously acquired accounting and computer skills. In addition to spreadsheet techniques and applications using Excel, the student will learn to analyze financial statements using lesser-known techniques (e.g., The DuPont Model) and design financial models and dashboards using data analytics tools.

Course content

1. Review basic spreadsheet and Microsoft Excel concepts.

Basic: worksheet environment, navigation, formatting, entering data/formulas, editing
Intermediate: cell references, formulas, what if" analysis, charts and graphs
Advanced: financial functions, specialized functions, table lookup, pivot tables and pivot charts, multi-sheet workbooks, importing from other sources, data forms, dashboards, and templates

2. Review and apply basic accounting concepts (e.g., balance sheet, income statement).

Reading and interpreting financial statements
Users of the financial statements and their needs

3. Apply Microsoft Excel concepts to accounting (e.g., financial statements, financial analyses, and supporting schedules), including a complete accounting worksheet and set of financial statements.

4. Apply the Data Analytics Process.

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

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

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

6. Design and create a visualization/dashboard using an appropriate data analytics tool.

Evaluate existing data
Create visualization/dashboard for key ratios / to cater to different users of the financial statements
Define and calculate key ratios for a business owner
Design charts and graphs for different users of the financial statements
Present dashboard

7. Interpret and analyze pre-generated reports (e.g., developed through generative artificial intelligence tools) on a company’s financial health and assess its accuracy.

Learning activities

Lecture and/or seminar

All methods of instruction apply to in class, hybrid and/or online modes of learning.

Means of assessment

Assessment will be based on course objectives and will be carried out in accordance with the Douglas College Evaluation Policy. An evaluation schedule is presented at the beginning of the course. This is a graded course.

Group Project(s):

A minimum of one group data analytics or Microsoft Excel project 30%

Individual Activities:

In-class activities, homework assignments, and data analytics/Microsoft Excel projects 30%
Final Exam 40%

Students must write all examinations in order to obtain credit for the course.

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 the course, the successful student should be able to:

Create finance- and accounting-related spreadsheets and charts by enhancing previously acquired finance, accounting, and computer skills
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
Create, interpret, and analyze dashboards
Apply the data analytics process to communicate insights and track outcomes

Textbook materials

Richardson, Teeter, Terrall. Data Analytics for Accounting. Latest International Edition

and/or

Storytelling with Data: A Data Visualization Guide for Business Professionals. Knaflic. Latest Edition

and/or

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

Requisites

Prerequisites

(ACCT 1110 with a grade of C+ or better OR ACCT 1210 with a grade of C or better OR ACCT 1235 with a grade of C or better) AND (CSIS 1190 with a grade of C or better or CSIS 2200 with a grade of C or better.)

Corequisites

None

Equivalencies

None

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.

January 2025 (Current)

Course Transfers to Other Institutions

Below are current transfer agreements from Douglas College to other institutions for the current course guidelines only. For a full list of transfer details and archived courses, please see the BC Transfer Guide.

Institution	Transfer details for ACCT 1220
Langara College (LANG)	LANG FMGT 2308 (3)
Simon Fraser University (SFU)	No credit
Thompson Rivers University (TRU)	TRU ACCT 2280 (3)
University Canada West (UCW)	UCW ACCT 1XX (3)
University of British Columbia - Okanagan (UBCO)	No credit
University of Northern BC (UNBC)	No credit
University of the Fraser Valley (UFV)	UFV BUS 1XX (3)
University of Victoria (UVIC)	No credit