Chapter 6 Summary

Chapter 6 focuses on applying data analytics to audit inventory for a fictional company called Bibitor. The chapter uses the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology to approach an audit data analytics (ADA) problem.

The chapter begins by outlining learning objectives, which include importing large datasets, using summary statistics, developing queries to generate aggregate variables, merging data from different datasets, and applying these skills to understand a company's business and assess risks of material misstatement in inventories. It then introduces the Bibitor case study, a retail liquor company, and presents an audit objective related to assessing the risk of material misstatement in inventory valuation.

The document provides step-by-step instructions on using Alteryx software to load, prepare, and analyze data from multiple related tables including sales, inventory, and product data. It covers concepts such as aggregating data, identifying outliers, and comparing average selling prices to average acquisition costs to identify potential inventory write-down issues. The chapter includes several in-chapter practice problems and ends with takeaway points emphasizing the importance of leveraging database concepts and data management tools in addressing common audit problems. It also includes an appendix showing an example of an audit working paper documenting the planning, performance, and evaluation of the inventory ADA.