This teaching case covers technical and non-technical concerns about data mining enabled by the creation of a data warehouse by the California Franchise Tax Board (CFTB). CFTB used data mining to analyze data collected from federal, state and municipal agencies and other organizations to identify residents who under-report income or fail to file tax returns. The case presents different stakeholders’ privacy, financial, technical and political concerns regarding the use of data obtained from an array of sources. The case is aimed at an undergraduate or MBA/MS course on IS Management, Data Management/Warehousing or Information Privacy. It could also be used to study IT and public policy, or E-government. It provides an opportunity for students to consider how social and political factors interact with technical challenges in inter-enterprise relationships. It also offers an opportunity to consider the value of data in relation to both the financial and non-financial costs of obtaining it.
Fedorowicz, Jane and Gogan, Janis L., "Mining Data to Catch Tax Cheats" (2009). ICIS 2009 Proceedings. 128.