Just stumbled upon Data Discovery (Spotlight), a research report available for free (downside: you need to register to download it):
Data discovery or, more precisely, data relationship discovery, is of fundamental importance to a wide range of functions ranging from business intelligence through master data management to data governance and data archival. Nevertheless, it has not traditionally been treated as a market or requirement in its own right. This is largely because the tools that have been available to discover data relationships have all been data profiling tools which, in turn, have been closely associated with data quality rather than more general-purpose usage. However, that is no longer the case: there are now a number of products on the market that can discover data relationships that do not fall within the category of either data profiling or data quality. As a result, it is time to consider the importance of data discovery, and its requirements, as a market in its own right.
In this paper we will discuss what data discovery is, why it is important, what sort of functionality you should be looking for in a data discovery product and the different approaches to data discovery that are currently available.
While you are there, you may also consider to download Data Discovery (Market Update):
This is the first of four Market Updates on data discovery, data profiling, data cleansing and matching, and data quality platforms respectively. Since data discovery is a new market sector we need to make a distinction between it and data profiling. We define data discovery or, more correctly, data relationship discovery, as “the discovery of relationships between data elements, regardless of where the data is stored”. Data profiling tools do this but they also perform statistical analysis against data sources for such things as the number of null values that are specifically designed to assist data cleansing processes. Conversely, there are data discovery tools that are not data profiling tools.