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Unformatted text preview: Data Discovery Market Update Figure 1: The highest scoring companies are nearest the centre. The analyst then defines a benchmark score for a domain leading company from their overall ratings and all those above that are in the champions segment. Those that re- main are placed in the Innovator segment if their innovation rating is over 2.5 and Challenger if it is less than 2.5. The exact position in each segment is calculated based on their combined innovation and overall score. C h ampio n I n n o v a t o r C h a l l e n g e r Ataccama BDQ CA Composite Datactics DataFlux Datamentors Datiris Embarcadero Exeros Global IDs IBM Informatica Microsoft Pervasive REVER SAP Business Objects Sypherlink Talend Trillium x88 Introduction 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. Moreover, data profiling is closely associated with data quality but data discovery has far wider application than just data quality. For example, data discovery is important when implementing MDM (master data management) apart from its value in supporting data quality; it can be used to complement data modelling tools; it may be employed for business intelligence purposes; and it has a significant role to play in supporting data migrations, data archival and data governance, amongst others. For a detailed discussion of this topic see the Bloor Research Spotlight Paper on this subject that is being published to accompany this Market Update. As a result of these two considerations: that data discovery isn’t only provided by data profiling tools and that the utility of data discovery isn’t limited to data quality environments, we believe that data discovery should be treated as a market in its own right. Key market issues There are, essentially, four different approaches to discovering data relationships. The oldest, and least efficient (at least if you working with more than one data source), is data modelling. Using tools of this type you can reverse engineer existing database schemas in order to discover the relationships defined within that schema....
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- Spring '09
- Data Management, Data Quality, data cleansing, data discovery