Microsoft Word - Data Quality1

Features that buyers should evaluate in a data quality tool include: Domain-agnostic data quality, for managing different kinds of non-customer data, such as product and financial information. International language and data format support, required for growing or global companies. Real-time monitoring service capabilities and tools that support both batch-oriented, bulk data cleansing as well as real-time, embedded data cleansing. Ease of implementation and usability, especially for certain functions, such as data profiling, which should be accessible to non-technical business people. Completeness of functionality and a single tool that can handle various data quality activities such as profiling, matching and cleansing.

"The vendors that rated strongest on vision [both leaders and visionaries] are really pushing the envelope in two areas. One is the notion of ongoing, real-time monitoring of data quality -- technology that's good at building rules that you can deploy in operational systems, rather than after-the-fact cleansing," Friedman said. "Also, their technology is very domain agnostic -- it's not just about customer data, it's about all kinds of data."

Firstlogic (now owned by BusinessObjects), DataFlux, IBM and Trillium were named the market leaders. Those labeled "visionaries" include Informatica, because of its purchase of Similarity Systems, and Human Inference, which offers a single platform with multiple functions and international support, Friedman said. No vendors were identified in the challenger category of the study.