Chapter 7 Summary

Chapter 7 focuses on applying data analytics to tax issues, specifically worker classification problems. The chapter uses a fictional media company called NewPub as a case study and applies the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology to approach a tax analytics problem.

The chapter begins by outlining learning objectives, which include translating business problems into data analytics problems, understanding data limitations, working with relational databases, performing necessary data transformations, and communicating findings to stakeholders. It then introduces the NewPub case study, where the company needs to determine if its independent contractors are properly classified according to IRS guidelines.

The document provides step-by-step instructions on using Alteryx software to load, prepare, and analyze data from multiple related tables including job, worker, invoice, itemized amount, and pay item data. It covers concepts such as importing and reviewing data, establishing relationships between tables, merging datasets, and filtering data to identify potential IRS guideline violations. The chapter includes several in-chapter practice problems and ends with takeaway points emphasizing the importance of taking a systematic approach to data analytics and understanding data limitations. It also previews upcoming chapters on forecasting applications in accounting.