Integrating product data carries a tremendous value, but cleanly integrating that data across multiple applications, data stores, countries and businesses can be as elusive a goal as catching the famed Looney Tunes character. In an Information Management article titled 5 Reasons Why Product Data Integration is Like Chasing Roadrunners. Paige Roberts, marketing manager at Pervasive, [...]

Pervasive recently recognized Logica Sweden as the winner of the 2011 InnovatioNEXT Awards at the annual European Data Innovation Summit that took place in early February in London. Logica Sweden was named the 2011 winner by a panel of Pervasive technologists and executives, with recognition going to the winner who best exemplifies innovation. Logica Sweden [...]

Mike Hoskins, CTO of Pervasive, talks about data matching and the expensive and difficult problem of resolving data duplicates. He touches on fuzzy matching, probabilistic rule systems, and some other strategies to deal with some of the killer problems in duplicate data like Unicode support, international data, product data, …

The goal of every data quality project is the same: to make the data more useful. The thing is, to be useful, the data first has to be there. One of the most confounding aspects of a data quality project is incomplete data. There are big holes in your data, incomplete addresses, missing emails, partial phone numbers, and product data missing half the attributes. You know exactly how bad it is. But now what?

Data profiling and remediation of poor quality data requires extra manpower to build, extra thought and planning to determine what metrics to use, extra software to make it happen. Why bother?