Scenarios for information analysis
These scenarios show how different organizations used InfoSphere® Information Analyzer to facilitate data integration projects by understanding their data.
Government: Tax collection
The tax authority of a large government needed to modernize its tax collection system. The tax authority was responsible for collecting taxes of all types from eligible taxpayers, including individuals, organizations, and vehicle owners. Tax data was collected into a central repository, but after several decades, the details of taxpayers were in various formats such as flat files, spreadsheets, and relational databases. Taxpayer data often included multiple tax identifiers, variation in spellings of a name, or the same identifier was assigned to multiple taxpayers. Consolidating data resulted in multiple data quality issues that impeded progress and slowed development of an updated solution.
The tax authority implemented InfoSphere Information Analyzer to profile data and confirm potential data quality issues in taxpayer data. In phase one of the implementation, fifty percent of the data quality issues in the income tax segment were solved by using InfoSphere DataStage® and QualityStage®. In phase two, issues in sales tax data were resolved. In phase three, the income tax and sales tax databases were consolidated to form a single database. Fixing data quality issues and consolidating data helped the tax authority to identify individuals who were delinquent in paying taxes or who listed their assets under different names. This solution helps to detect fraud and avoid future exploitation of the tax code.
Transportation services: Data quality monitoring
A transportation service provider develops systems that enable its extensive network of independent owner-operators to remain competitive in the market. The owner-operators were exposed to competition because they were unable to receive data quickly, and executives had little confidence in the quality of the data that they received. Because the owner-operators had to manually intervene to reconcile data from multiple sources, productivity slowed excessively.
The owner-operators used InfoSphere Information Analyzer to better understand and analyze their legacy data. By increasing the accuracy of their business intelligence reports, the owner-operators restored executive confidence in their company data. Moving forward, the owner-operators implemented a data quality solution to cleanse their customer data and identify trends over time, further increasing their confidence in the data.
Food distribution: Prepare infrastructure rationalization
A leading US food distributor had more than 80 separate mainframe, SAP, and JD Edwards applications supporting global production, distribution, and customer relationship management (CRM) operations. This infrastructure rationalization project included planning for CRM, order-to-cash, purchase-to-pay, human resources, finance, manufacturing, and supply chain operations. The company needed to move data from these source systems to a single target system.
The company used InfoSphere Information Analyzer to profile its source systems and create master data for key business dimensions, including customer, vendor, item (finished goods), and material (raw materials). The company plans to migrate data into a single master SAP environment and a companion SAP business intelligence reporting platform.