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A description of data dictionary systems is given in Chapter 12.
Assume that there are two organizations, each having a separate data dictionary.
Data Dictionary: contains definitions for all the possible fields used by the model.
Similarly an export data dictionary was set up for exporting.
Data Dictionaries define the business rules for each table in your database.
This can be a subset of the fields as defined in the data dictionary.
Yet this information is usually available in some data dictionary view that can be queried by object name.
The data dictionary is like that of structured analysis.
It has an active data dictionary and gives a relational view of the database.
An import data dictionary was set up to map fields to the required location.
These differences must be reconciled and recorded in the data dictionary (see Chapter 12).
Here you have Data Dictionary classes which are the core of the product.
An active data dictionary is automatically updated as changes occur in the database.
Metadata repositories used to be referred to as a data dictionary.
A representation term is commonly referred to as a class word by those familiar with data dictionaries.
Using a data dictionary approach to store and retrieve package and dependency information.
Other technical documentation like entity diagrams, data dictionary will also be produced in this phase.
These forms can be pre-drawn using software tools and their contents automatically added to the data dictionary.
Differences are hidden in the data dictionary.
Without a data dictionary, however, a database management system cannot access data from the database.
A data dictionary document also may include further information describing how data elements are encoded.
Schemas are generally stored in a data dictionary.
Which method is used may be determined by a referential integrity constraint defined in a data dictionary.
A passive data dictionary must be manually updated.
It includes a data dictionary of 86 data elements and covers device survivability.