BA 261 - Introduction to Data Analytics for Accounting
Description
This course introduces students to the fundamentals of data analytics in accounting. Students will explore the processes involved in acquiring, managing, and analyzing data to enhance decision-making in accounting. The course covers a wide range of analytical techniques, from descriptive to predictive and prescriptive analytics, and emphasizes the importance of data-driven insights in solving accounting problems. By the end of the course, students will be able to apply these analytical techniques to real-world accounting scenarios, enabling better financial planning, forecasting, and reporting.
Credit Hours: 3
Contact Hours: 3
Prerequisites/Other Requirements: C or Higher in one of the following courses: BA 156 or BA 256
English Prerequisite(s): None
Math Prerequisite(s): None
Course Corequisite(s): None
Academic Program Prerequisite: None
Consent to Enroll in Course: No Department Consent Required
Dual Enrollment Allowed?: Yes
Number of Times Course can be taken for credit: 1
Programs Where This Course is a Requirement:
Accounting, A.B., Pre-Accounting, A.B. (3+1, Davenport University)
Other Courses Where This Course is a Prerequisite: None
Other Courses Where this Course is a Corequisite: None
General Education Requirement:
None
General Education Learner Outcomes (GELO):
NA
Course Learning Outcomes:
1. Apply Data Analytics Frameworks: Use a structured approach to acquire, manage, prepare, and analyze accounting data to support informed decision-making.
2. Perform Descriptive Analytics: Analyze accounting data to summarize and identify key trends, providing a clear view of historical business performance.
3. Perform Diagnostic Analytics: Detect anomalies and investigate the underlying causes of trends or irregularities in accounting data.
4. Implement Predictive Analytics: Use forecasting and statistical models to predict financial outcomes and assess potential business scenarios.
5. Utilize Prescriptive Analytics: Apply optimization techniques and scenario analysis to recommend actionable strategies for improving business outcomes.
6. Communicate Data Insights Effectively: Develop clear visualizations and reports that communicate the results of data analyses to stakeholders.
Course Outline:
I. Introduction to Data Analytics in Accounting
I.A. Explain how increasing data availability and computerization are shaping the accounting profession.
I.B. Describe critical thinking skills accountants must develop to address accounting questions with data.
I.C. Describe the AMPS Model and explain its role in data analytics.
I.D. Describe the common visualization types and explain their role in communicating results.
II. Mastering the Data
II.A. Define Big Data and its characteristics.
II.B. Describe available accounting and non-accounting data sources.
II.C. Explain the use of data dictionaries, databases, and relational database concepts.
II.D. Extract and prepare data for analysis using Excel, Tableau, and databases.
III. Descriptive Analytics
III.A. Define and illustrate descriptive analytics with examples.
III.B. Analyze data using vertical, horizontal, and DuPont analysis.
III.C. Summarize results and trends using visualizations.
IV. Diagnostic Analytic
IV.A. Define diagnostic analytics and its role in identifying anomalies.
IV.B. Use drill-down and statistical techniques to discover patterns and relationships.
IV.C. Explore appropriate visualizations for diagnostic analytic.
V. Predictive Analytics
V.A. Define predictive analytics and explain its purpose.
V.B. Use classification, regression, and time-series analysis to forecast outcomes.
V.C. Integrate machine learning techniques in predictive modeling.
V.D. Visualize predictive analytics results effectively.
VI. Prescriptive Analytics
VI.A. Define prescriptive analytics and its connection to other analytics types.
VI.B. Apply optimization, marginal analysis, and scenario analysis.
VI.C. Use goal-seek and sensitivity analysis to evaluate business decisions.
VI.D. Visualize results for actionable decision-making.
VII. Financial Statement Analysis
VII.A. Define and outline the purpose of financial statement analysis.
VII.B. Address financial questions using descriptive, diagnostic, predictive, and prescriptive analytics.
VII.C. Characterize reporting methods for financial statement analysis results.
VIII. Managerial Accounting Analytics
VIII.A. Define managerial accounting analytics and its role in decision-making.
VIII.B. Address cost and performance questions using descriptive, diagnostic, predictive, and prescriptive techniques.
VIII.C. Explore reporting methods for managerial analytics results.
IX. Effective Communication of Data Insights
IX.A. Develop clear visualizations and reports to communicate results.
IX.B. Apply storytelling principles to present analytics findings to stakeholders.
X. Applying the AMPS Mode
X.A. Demonstrate the completed AMPS model in addressing accounting questions.
X.B. Integrate the framework into real-world decision-making scenarios.
Approved for Online and Hybrid Delivery?:
Yes
Instructional Strategies:
Mediated Instruction: 30-50%
Independent Reading and Study: 10-20%
Project-Based Learning: 30-40%
Discussion: 10-20%
Reflection Activities: 5-10%
Mandatory Course Components:
None
Equivalent Courses:
None
Accepted GRCC Advanced Placement (AP) Exam Credit: None
AP Min. Score: NA
Name of Industry Recognize Credentials: None
Course-Specific Placement Test:
Course Aligned with ARW/IRW Pairing: NA
Mandatory Department Assessment Measures:
None
Course Type:
Program Requirement- Offering designed to meet the learning needs of students in a specific GRCC program.
Course Format:
Lecture - 1:1
Total Lecture Hours Per Week: 3
People Soft Course ID Number: 105326
Course CIP Code: 52.9999
Maximum Course Enrollment: 24
Course Software Utilized: Excel, Tableau, Power BI, Orange Data Mining
School: School of Business & Industry
Department: Business
Discipline: BA
First Term Valid: Fall 2025 (8/1/2025)
1st Catalog Year: 2025-2026
Name of Course Author:
Brian Daily
Faculty Credential Requirements:
Master’s Degree (GRCC general requirement), Professionally qualified through work experience in field (Perkins Act or Other) (list below)
Faculty Credential Requirement Details:
The instructor must have a knowledge of accounting and related work experience, as well as teaching experience.
Course Review & Revision Year: 2029-2030
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