The need to manage enterprise data has been coming into increasingly sharp focus for some time. Years ago, data sat in silos attached to specific applications. Then came the network, with data becoming available across applications, departments, subsidiaries and enterprises. Throughout these developments, one underlying problem has remained unsolved: data resides in thousands of incompatible formats and cannot be systematically managed, integrated, unified or cleansed.
Although multiple data technologies such as various legacy formats, relational and XML are in use, the most challenging incompatibility arises from semantic differences in the structure or schemas of data. Each and every data asset has its own taxonomy of business entities, such as different ways of segmenting products or customers and its own vocabulary for describing these entities. In total, a typical medium or large enterprise will often count thousands of data formats among its possessions. Moreover, the rules relating these formats to one another are recreated manually and hard-coded time and again.
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