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The states of a created conceptual schema are transformed into an explicit mapping, the database schema. This describes how real-world entities are modeled in the database. "A database schema specifies, based on the database administrator 's knowledge of possible applications, the facts that can enter the database, or those of interest to the ...
Whether the database design used the integrity constraint based keys of the IDEF1X model as database access keys or indexes was an entirely separate decision. The precision and completeness of the IDEF1X models was an important factor in enabling the relatively smooth transformation of the models into database designs.
Functional dependencies however should not be confused with inclusion dependencies, which are the formalism for foreign keys; even though they are used for normalization, functional dependencies express constraints over one relation (schema), whereas inclusion dependencies express constraints between relation schemas in a database schema.
Constraints ("simple types") can be defined for the textual content of elements and attributes, for example to specify that they are numeric or contain dates. A wide repertoire of simple types are provided as standard, and additional user-defined types can be derived from these, for example by specifying ranges of values, regular expressions ...
A table in a SQL database schema corresponds to a predicate variable; the contents of a table to a relation; key constraints, other constraints, and SQL queries correspond to predicates. However, SQL databases deviate from the relational model in many details , and Codd fiercely argued against deviations that compromise the original principles.
Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.
The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects.
The logical schema was the way data were represented to conform to the constraints of a particular approach to database management. At that time the choices were hierarchical and network. Describing the logical schema, however, still did not describe how physically data would be stored on disk drives. That is the domain of the physical schema.