Therefore, in order to be successful, it is essential for
an enterprise to make right business decisions and to make them fast. Business
decisions are taken on the basis of analyses of the past and current condition of
an enterprise as well as market analysis and predictions for the future. To this end,
various business operational data collected during the lifetime of an enterprise are
analyzed. Typically, operational data are stored within an enterprise in multiple data
storage systems (subsystems) that are geographically distributed, are heterogeneous
and autonomous.
The heterogeneity of data storage systems means that they come from different
software vendors; they are implemented in different technologies (e.g., C, C++, .Net,
Java, 4th generation programming languages); they offer different functionality (e.g.,
fully-functional databases, ODBC data sources, spreadsheets, Web pages, text files);
they use different data models (e.g., relational, object-relational, object-oriented,
semistructured) and different storage techniques; they are installed on different
operating systems and use different communication protocols.
The autonomy of data storage systems implies that they are often independent from
each other and remain under separate, independent control; that is, a local system??™s
administrator can decide which local data are to be accessible from the outside of
the system.
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