Big Data Investigating Fraud

(Part 1 of Data Analytics Project #2)

Many retailers have return policies that may allow customers to return merchandise several months after a purchase. However, a common requirement is that the item returned must have been purchased at one of the companys stores and must be an item that is sold by the company. In some cases return errors can occur such that a cashier accepts an item for return that is not sold by the store. If the store does not require a receipt, these returns can be done intentionally as a way to pilfer money from the company. These types of returns may also be the result of collusion between a customer and a store employee to pilfer money from the store. To identify if this is happening, inventory discrepancies can be investigated using data analytics.

The purpose of this exercise is to use the new skills demonstrated in this chapter to identify inventory return discrepancies for a hypothetical retailer. Begin the exercise by opening the excel file named Excel Lab M6 Big Data. Questions that are preceded with the letters KO indicate you must only use your keyboard and not your mouse to execute the required skill.