Data Independence and Data Abstraction

Data Independence and Data Abstraction

What is Data Independence?

The capacity to utilize the database without knowing the representation elements is known as data independence.

It is the ability to change the mapping of one level of a database framework without having to change the mapping at the next significant level.

Reasons for Data Independence

There are reasons for data independence are as follows:

• To allow the DBA to make changes in the content, location, representation, and organization of a database without causing reprogramming of application programs that use the database.
• To allow the supplier of data processing equipment and software to introduce new technologies without causing reprogramming of the customer’s applications.
• To facilitate data sharing by allowing the same data to appear to be organized differently for different application programs.
• To provide the centralization of control needed by the database administrator (DBA) to ensure the security and integrity of the database.

Types of Data Independence

There are two types of data independence are:

Logical Data Independence

Logical Data Independence defines that the global logical architecture of data may be changed without changing the application programs.

Hence logical data independence is the capacity to change the logical conceptual mapping without generate software functions to be revise or any change to the external mapping.

Changes or alterations in the conceptual mapping may contain the addition or deletion of new entities, attributes, or relationships. These changes should be possible without having modification to existing external schemas.

Physical Data Independence

Physical Data Independence defines that the physical structure and organization of the information may be changed without changing either the global logical structure of the information or the application programs.

Hence, Physical data independence is the capacity to change the internal mapping without generate any change in the conceptual mapping. Alteration in the internal mapping might include:

• Using new storage devices.
• Using different data structures.
• Switching from one access method to another.
• Utilizing several record organizations or storage architecture.
• Changing Indexes

The changes noticed above should be feasible without having to change the conceptual or external mappings.

The figure illustrates the concept of logical and physical independence.

What is Data Abstraction?

Data Abstraction refers to the process of hiding irrelevant details from the user.

There are three levels of abstraction:

Physical level:

This is the shortest level of data abstraction. It represents how the record is saved in the database. We can get the complex data structure elements at this level.

Logical level:

This is the central level of the three-level data abstraction mechanism. It represents what record is saved in the database.

View level:

This is the topmost level of data abstraction. This level represents the client interaction with the database framework.

The primary objective of data abstraction is achieving data independence to store time and value needed when the database is changed or altered.

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