Data Abstraction
Abstraction is the simplification mechanism use to hide superfluous details of a set of objects. It allows one to concentrate on the properties that are useful to the application.
Abstraction is the act of removing certain distinctions between object so that we can see commonalities. Here only the selected properties of the object a made visible to the outside world and their internal representation hidden.
Example of data Abstractions is University database. Where those data will be show which is required for to show us, but how data is working inside database that how data are transferring & what logics are using to maintain database that all never will be shown.
Level of Abstraction :
There are three levels of data abstraction: --
1. External level or View level
2. Conceptual level or Logical level
3. Internal level or Physical level
1. External or View level : This is the highest level of abstraction. Despite the use of simple structure at logical level. Some complexity remains because of the large size the database. Many users of the database system will not be concerned with all this information. Only a part of the actual database is viewed by the users. User view data in the form of row and column.
2. Conceptual or Logical level : This is mid level of abstraction. It describes what data are stored in the database and what relationships exist among those data. At this level, the information available to the user at the view level is unknown. We can store the various attributes of an student and relationships, example with the teacher can also be stored.
3. Physical or Internal level : This is the lowest level of data abstraction. It tells how the data is actually stored in memory. The access methods like sequential or random access & file organization methods like B+ tree, hashing used for the same.
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