17 - Data quality and business rules in practice

Abstract

This chapter reviews the data quality rules in a context that demonstrates ways to actually use these rules. The implementation of a data quality rules process can add significant value to different operating environments. These rules can be turned into Structured Query Language (SQL) queries and can be integrated into a rules engine. The chapter also illustrates the integration of approximate matching and scoring rules into "fuzzy" cleansing applications through the combination of approximate rules with other rules. Measurements and triggers also help in describing a full-fledged data quality application before writing a stitch of code. Finally, the chapter presents some implementation paradigms of data quality rules such as data quality and the transaction factory; data quality and the data warehouse; data quality and electronic data interchange (EDI); and data quality rules used to drive content-dependent user interfaces. Data quality rules can help automate the generation of a user interface (UI) based on maintaining a high level of data quality.