This paper is the first in a series of case studies, which complement the data mastering white paper described above by examining the practical use and implementation of Silver Creek Systems' semantically-based DataLens System in specific customer situations. Silver Creek Systems has customers across a range of industries but in this paper we have chosen to focus on healthcare, though the problems identified, experience and lessons learned are applicable across many industries. While Silver Creek Systems has a number of customers in the healthcare sector, including Cardinal Health, the two customers we interviewed in preparing this paper both prefer to remain anonymous.
Since both companies happen to be in healthcare, this paper will first examine the types of data quality problems that are common within the healthcare market and how Silver Creek addresses these, before moving on to consider the particular issues facing each of the companies interviewed. We will conclude with some observations on the success (or otherwise) of these projects and their implications.