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data independence

Techniques that allow data to be changed without affecting the applications that process it. There are two kinds of data independence. The first type is data independence for data, which is accomplished in a database management system (DBMS). It allows the database to be structurally changed without affecting most existing programs. Programs access data in a DBMS by field and are concerned with only the data fields they use, not the format of the complete record. Thus, when the record layout is updated (fields added, deleted or changed in size), the only programs that must be changed are those that use those new fields.

Data Independence for Processing
The second type of data independence relates to processing and refers to miscellaneous data used in programs that might change in the future, such as discount rates, product descriptions and error messages. Such data should be stored in a database and not "hard wired" into the code of the program. When values change, only the database item is altered, a much simpler task than recompiling numerous programs.

Data Independence for Data
Program #1 reserves space for the entire record (fields A to K). If the record format is changed, the space must be changed. Program #2 calls the DBMS to deliver just the fields it uses (D G H K). It still reserves space, but unless a field has been resized, it is not affected by other field changes. Program #3 is fully independent of the data structure. It calls for data by field name, and the DBMS allocates the space at runtime.

Data Independence for Processing
Program #1 uses a hard-coded value to test credit limit. To change the limit, the program must be recompiled. Program #2 retrieves the credit limit from a database. To change it, only the database must be updated, a simpler task.

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Before/After Your Search Term
data forkdata integrity
data formatdata interchange format
data furnacedata item
Data Generaldata kidnapping
Data General Onedata lake
data glovedata latency
data glutdata leakage
data governancedata legibility
data hidingdata library
data hygienedata life cycle management

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