Sep 27, 2022
ACC 189 - Introduction to Data Analytics for Accounting
Course Department: Business
Last Date of Approval: 10/19/21
Total Lecture Hours: 45
Total Lab Hours: 0
Total Clinical Hours: 0
Total Work-Based Experience Hours: 0
Business operations are increasingly relying on data-driven decision-making practices. This requires accountants to ask the right questions to acquire, manage, analyze, and display large, quantitative data sets appropriate for the identified problem. This course will introduce students to important terminology and concepts in data analytics while utilizing computerized programs and applications for data extraction and evaluation. Students will be able to use quantitative data in real-time problem identification, decision-making, and problem-solving.
Prerequisites: ACC 146 and CSC 116
Mode(s) of Instruction: Face to Face
Credit for Prior Learning: There are no Credit for Prior Learning opportunities for this course.
Course Fees: None
Common Course Assessment(s): None
Student Learning Outcomes and Objectives:
Student Learning Outcomes/Unit Objectives:
- Students will explain the importance of answering questions using data-driven information.
- Utilize Bloom's Taxonomy when solving basic to advanced accounting problems.
- Describe and master the AMPS model.
- Students will identify specific accounting problems and the relative data required to solve them.
- Evaluate accounting information and reports to determine important questions that need addressed.
- Address accounting questions by determining the pertinent data needed to explain, solve, and make recommendations.
- Use multiple methods and statistical techniques to analyze data to discover patterns, links, and relationships.
- Students will extract and analyze large quantitative data sets using computer applications.
- Utilize Microsoft Excel and Tableau to extract data.
- Students will summarize data gathered and report findings to assist stakeholders to make sound and timely business decisions.
- Explain to management and non-accounting users the process completed, data-based results, and recommendations.
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