Data modeling is routinely used in conjunction with a database management system. Data that has been modeled and made ready for this system can be ...

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Note added at 25 mins (2011-06-21 08:28:25 GMT)
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Data modeling is a method used to define and analyze data requirements needed to support the business processes of an organization. The data requirements are recorded as a conceptual data model with associated data definitions. Actual implementation of the conceptual model is called a logical data model. To implement one conceptual data model may require multiple logical data models. Data modeling defines not just data elements, but their structures and relationships between them Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. The use of data modeling standards is strongly recommended for all projects requiring a standard means of defining and analyzing data within an organization, e.g., using data modeling:
to manage data as a resource;
for the integration of information systems;
for designing databases/data warehouses (aka data repositories)

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Databases are growing so large and queries on those databases so complex that it is often impractical and sometimes unnecessary to access all of the data relevant to a query. In some cases, a user is interested in finding overall 2 trends or patterns, in which case approximate answers within some margin of error will suffice. One way to speed up such queries is to perform the query on a random sample of the database.