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Lecturer(s)
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Jemberu Etsub Tekola, Ph.D.
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Dehning Bruce, assoc. prof. Ph.D.
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Course content
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Introduction to Alteryx and Data Analytics Industry Analysis With Data Analytics Strategic Analysis With Data Analytics Customer Analysis With Data Analytics Introduction to Relational Databases Data Analytics for Internal Audit Data Analytics for Inventory Analysis Data Analytics for Tax Analytics Forecasting With Data Analytics
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Learning activities and teaching methods
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Lecturing, Dialogic (Discussion, conversation, brainstorming), Simple experiments, Practice exercises, Teamwork, Translation analysis, Analysis of a presentation
- Home preparation for classes
- 33 hours per semester
- Term paper
- 78 hours per semester
- Participation in classes
- 39 hours per semester
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| prerequisite |
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| Knowledge |
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| - Basic knowledge of Financial Accounting. - Understanding introductory Finance terms. |
| - Basic knowledge of Financial Accounting. - Understanding introductory Finance terms. |
| learning outcomes |
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| - identify business applications where data mining concepts and tools can be used to answer accounting questions |
| - identify business applications where data mining concepts and tools can be used to answer accounting questions |
| - describe data structures, sources, and methods for assessing data quality |
| - describe data structures, sources, and methods for assessing data quality |
| - explain data mining classification and prediction models in plain English |
| - explain data mining classification and prediction models in plain English |
| - define the applications of data analytics in financial accounting, managerial accounting, auditing, and taxation |
| - define the applications of data analytics in financial accounting, managerial accounting, auditing, and taxation |
| - understand how to evaluate analytical models using mathematical and logical techniques |
| - understand how to evaluate analytical models using mathematical and logical techniques |
| - describe how to translate data into meaningful business information |
| - describe how to translate data into meaningful business information |
| - identify the principles behind competitive advantage analysis using financial data |
| - identify the principles behind competitive advantage analysis using financial data |
| Skills |
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| - collect, extract, clean, and transform data for analysis using Alteryx |
| - collect, extract, clean, and transform data for analysis using Alteryx |
| - link data in organized and meaningful ways to form relational databases |
| - link data in organized and meaningful ways to form relational databases |
| - analyze financial performance through techniques like ROA decomposition |
| - analyze financial performance through techniques like ROA decomposition |
| - create forecasting models to predict business objectives |
| - create forecasting models to predict business objectives |
| - identify potential fraud or errors through data analysis and comparison of expected versus actual results |
| - identify potential fraud or errors through data analysis and comparison of expected versus actual results |
| - communicate key findings from data analysis in a clear and professional manner |
| - communicate key findings from data analysis in a clear and professional manner |
| - apply data analytics techniques to solve problems in financial accounting, managerial accounting, auditing, and taxation |
| - apply data analytics techniques to solve problems in financial accounting, managerial accounting, auditing, and taxation |
| teaching methods |
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| Knowledge |
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| Activating (Simulation, games, dramatization) |
| Activating (Simulation, games, dramatization) |
| Exercises on PC |
| Exercises on PC |
| Individual work of students |
| Individual work of students |
| Practice exercises |
| Practice exercises |
| Text analysis |
| Text analysis |
| Skills |
|---|
| Activating (Simulation, games, dramatization) |
| Activating (Simulation, games, dramatization) |
| Exercises on PC |
| Exercises on PC |
| Individual work of students |
| Individual work of students |
| Practice exercises |
| Practice exercises |
| Text analysis |
| Text analysis |
| assessment methods |
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| Knowledge |
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| Analysis of the student's performance |
| Analysis of the student's performance |
| Analysis of works made by the student (Technical products) |
| Analysis of works made by the student (Technical products) |
| Grade (Using a grade system) |
| Grade (Using a grade system) |
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Recommended literature
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Baruti, R. Learning Alteryx: A beginner's guide to using Alteryx for self-service analytics and business intelligence. Packt Publishing, 2017. ISBN 978-1788392655.
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Bierman, H., Smidt, S. Financial Management for Decision Making. Washingto, 2003. ISBN 1-58798-212-9.
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Burkhow, J. Alteryx Designer: The Definitive Guide: Simplify and Automate Your Analytics. O'Reilly Media, 2023. ISBN 978-1098107529.
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Dehning, B., Stratopoulos, T., and Mohapatra, P. Accounting Analytics With Alteryx. 2025.
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Green, T. Alteryx for Accounting, Tax and Finance Professionals. 2021. ISBN 979-8578651236.
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Houghton, P. Data Engineering with Alteryx: Helping data engineers apply DataOps practices with Alteryx. Packt Publishing, 2022. ISBN 978-1803236483.
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Rohilla Shalizi, C. Advanced Data Analysis from an Elementary Point of View. 2025.
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