Accounting Data Analytics

Student Learning Outcomes, Goals, Objectives:

Students successfully completing this course will be able to:

• Define data analytics and explain why it is important for accounting and business.

• Describe the stages of the data analysis process.

• Describe how data is stored in and extracted from relational databases.

• Demonstrate how to develop descriptive, diagnostic, and predictive questions.

• Summarize data and analyses strategies in professional practice areas.

• Explain and apply extraction, transformation, and loading (ETL) techniques.

• Describe the foundational concepts of information modeling.

• Use visualization to communicate effectively.

• Apply critical thinking to data analysis interpretation.

• Explain how technology developments are impacting data analysis in accounting.

Course Grading Information:

Activity/Performance Measure	Percentage/Points
Analytics questions and exercises	10%
Analytics Practice Sets/Problems	20%
Analytics Cases (Projects)	20%
Two Mid-term Exams	20% (each 10%)
Final Exam + Analytics Assessment	30%
Total	100%

Attendance/Participation:

Attendence is required. More than two unexcused absences will result in a letter grade reduction.

Course Materials Purchased by the Students:

Data and Analytics in Accounting: An Integrated Approach. Ann C. Dzuranin, Guido Geerts, Margarita Lenk. Wiley. ISBN 13: 8220129319889. Wiley Plus access required.