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Accounting Analytics: Turning Data into Decisions

By Daniel Ames

1st Edition © 2028
Discipline:Accounting
Course:Accounting Information Systems
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"Accounting Analytics: Turning Data into Decisions" guides students on how analysts approach questions, gather and prepare data, perform meaningful analysis and communicate insights. The book's 15 chapters strike a balance between conceptual grounding and hands‑on application, providing a strong pedagogical design, illustrations and problem sets using tools such as Excel, Tableau, Alteryx and Python. Chapters build off of the CRAFT framework -- Consider, Retrieve, Analyze, Frame and Tell -- which provides students with an intuitive structure for thinking through analytics problems. Assessment materials include learning objectives, progress checks, discussion questions and in-depth labs or cases. The book aligns with analytics learning objectives from AACSB and the AICPA to integrate into modern accounting curricula and support programs that build data literacy and analytical confidence.

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AboutTable of contentsResourcesPricing & formatsRelated products

About this product

"Accounting Analytics: Turning Data into Decisions" guides students on how analysts approach questions, gather and prepare data, perform meaningful analysis and communicate insights. The book's 15 chapters strike a balance between conceptual grounding and hands‑on application, providing a strong pedagogical design, illustrations and problem sets using tools such as Excel, Tableau, Alteryx and Python. Chapters build off of the CRAFT framework -- Consider, Retrieve, Analyze, Frame and Tell -- which provides students with an intuitive structure for thinking through analytics problems. Assessment materials include learning objectives, progress checks, discussion questions and in-depth labs or cases. The book aligns with analytics learning objectives from AACSB and the AICPA to integrate into modern accounting curricula and support programs that build data literacy and analytical confidence.

All chapters include thought questions, multiple‑choice items and problems, plus advanced Excel, Tableau, Alteryx and Python labs in CNOWv2 to support deeper skill development.

Each chapter uses the CRAFT framework -- Consider, Retrieve, Analyze, Frame and Tell -- to guide students from raw data to decisions and help them see the bigger analytical process.

Hands‑on use of Alteryx, Python, Excel and Tableau gives students practical experience with tools that accountants and analysts rely on, connecting coursework to real workflows.

A dedicated chapter, “Tidy Data,” explains data preparation in depth, giving students clear guidance for cleaning, structuring and organizing data for effective analysis.

Table of contents

  1. 1. Introduction to Data Analysis.
  2. 2. Tidy Data.
  3. 3. Descriptive Statistics.
  4. 4. Data Visualization.
  5. 5. Probability and Statistical Inference.
  6. 6. Regression Analysis.
  7. 7. More Topics in Regression Analysis.
  8. 8. Logistic Regression.
  9. 9. Data Mining.
  10. 10. Robotic Process Automation (RPA).
  11. 11. Audit Analytics.
  12. 12. Tax Analytics.
  13. 13. Managerial Analytics.
  14. 14. Financial Statement Analytics.
  15. 15. Artificial Intelligence in Accounting.

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