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Registration for the Fall 2019 semester begins June 25.  Watch your email for more details.

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Data Analytics for Managers

Course Code: ACCT 3880
Faculty: Commerce & Business Administration
Department: Accounting
Credits: 3.0
Semester: 15 Weeks X 4 Hours per week = 60 Hours
Learning Format: Lecture, Online, Hybrid
Typically Offered: TBD. Contact Department Chair for more info.
course overview

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 use CaseWare IDEA software and Microsoft Excel.

Course Content

1.     Using DuPont Model and ratio analysis in order to analyze financial statements

·         Reading financial statements properly

·         Adjusting financial statements

·         Apply ratio calculation and DuPont Model

2.     Learn Caseware IDEA

·         Accessing different data files

·         Understanding data

·         Analyzing data:

    • Basic commands:  aging, summarization, stratification, pivot tables, gaps, duplicates, sorting, indexing, extracting
    • Using the equation editor for recalculation
    • Redefining source data using functions
    • Correlation and trend analysis

·         Working with multiple files:

    • Joining two files looking for matched or unmatched records
    • Searching for fields in multiple files 
    • Using visual connector to check for limits
    • Automating the process and reporting
    • History log, use of macros

  3.     Financial Modeling

·         Designing and creating an interactive financial model using Excel

·         Designing the layout of the model clearly and logically

·         Creating clearly defined inputs and assumption sections

·         Building powerful scenarios

·         Incorporating all related schedules

4. Designing and creating a Dashboard using Excel

·         Evaluating existing data

·         Defining Key Performance Indicators (KPI)

·         Calculating KPI

·         Designing charts and graphs for KPI

·         Presenting dashboard

Methods of Instruction

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

Means of Assessment

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

  • Analyze financial statements using DuPont Model
  • Compare and adjust financial statements
  • Demonstrate proficiency in using CaseWare IDEA software
  • Access and examine different data files
  • Analyze data patterns, identify discrepancies and extract unusual items
  • Create audit samples
  • Analyze data used in accounts receivable and/or payable aging reports, emphasizing data correlation and trend analysis
  • Analyze inventory for accuracy and risk exposure
  • 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

course prerequisites

(ACCT 1210 OR ACCT 1235) and CSIS 1190

Or currently active in the

-           PDD Accounting

-           PDD Data Analytics

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

-           PBD Accounting and Finance

-           PDD Accounting Studies

-           PBD Accounting

A minimum grade of C is required in all courses

Or permission of the instructor

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

curriculum 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 schedule and availability
course transferability

Below shows how this course and its credits transfer within the BC transfer system. 

A course is considered university-transferable (UT) if it transfers to at least one of the five research universities in British Columbia: University of British Columbia; University of British Columbia-Okanagan; Simon Fraser University; University of Victoria; and the University of Northern British Columbia.

For more information on transfer visit the BC Transfer Guide and BCCAT websites.

assessments

If your course prerequisites indicate that you need an assessment, please see our Assessment page for more information.