Computerized Accounting and Data Analytics

Curriculum guideline

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Course
ACCT 1220
Discontinued
No
Course code
ACCT 1220
Descriptive
Computerized Accounting and Data Analytics
Department
Accounting
Faculty
Commerce & Business Administration
Credits
3.00
Start date
End term
Not Specified
PLAR
No
Semester length
15 Weeks
Max class size
30
Course designation
None
Industry designation
None
Contact hours

In person: Lecture and/or Seminar: 1 X 3 hours per week OR 2 X 2hrs per week

or

Hybrid: minimum 50% in person and up to 50% online

or

Online: Synchronous and/or Asynchronous

Method(s) of instruction
Lecture
Seminar
Learning activities

Lecture and/or seminar

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

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 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
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.

 

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 

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

Which prerequisite

ACCT 3310.