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Data abstraction & Data independence
Data abstraction
Data abstraction implies concealing the subtleties that are irrelevant to the users. The database has a mind-boggling complex structure so to separate the information easily, several things are covered up and just pertinent part is open to the client through data abstraction. It is involved by designers to build proficiency for the recovery of data and to diminish the intricacy of given data.
It consists of three levels: Physical or Internal Level, Logical or Conceptual Level, View or External Level.
Three levels of data abstraction
Physical or internal level
It is the lowest level of abstraction which depicts how the data are really stored. It portrays complex low-level data structures in detail. i.e. provide insights regarding the data that are utilized for storage. Also gives records and groups to have command over the data and can be overseen without any problem.
Logical or conceptual level
This is the following more significant level of abstraction which depicts what data is precisely put away in the data set alongside the relationship that exists among those data. Here, the data is available in a type of table and the construction is moderately straightforward. At this level, the view level data is unknown.
View or external level
This is the most elevated level of abstraction. It depicts just a piece of the whole database. This level is available to make the access of data easy. Users view the data in form of rows and columns. It provides multiple views of the same database.
Data independence
The ability to modify a schema definition in one level without affecting the schema definition in the next higher level is called data independence. It consists of two levels − physical level and logical level.
Two levels of data Independence
Physical level
It is characterized as the ability to change the internal schema without changing the conceptual schema. It is utilized to isolate the conceptual level from the internal level. It happens at the logical interface levels.
For example − If we do any changes in storage system server, then conceptual structure of the database will not get affected.
Logical level
It alludes to the qualities of having the option to change the conceptual schema without changing the external schema. Any progressions made in the conceptual view won't influence the client's perspective on the data. Also, application programs need not be changed to adjust the conceptual schema. It is utilized to isolate the external level from the conceptual level. It happens at the user interface level.
Conclusion
In this article, we have explained data abstraction and data independence. Data abstraction consists of three parts,the first one is physical level which shows how the data are stored, second one is logical in which we get to the what data is getting stored and the third one, the view level which describes a part of entire database. On the other hand, data independence have only two parts in which the first one is physical level through which internal schema can be changed without harming conceptual schema and the second one is logical level where conceptual schema can be changed without changing external schema.
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