We know that the same thing, if viewed from different angles produces difference sights. Likewise, the database that we have created already can have different aspects to reveal if seen from different levels of abstraction. The term Abstraction is very important here. Generally it means the amount of detail you want to hide. Any entity can be seen from different perspectives and levels of complexity to make it a reveal its current amount of abstraction. Let us illustrate by a simple example.
A computer reveals the minimum of its internal details, when seen from outside. We do not know what parts it is built with. This is the highest level of abstraction, meaning very few details are visible. If we open the computer case and look inside at the hard disc, motherboard, CD drive, CPU and RAM, we are in middle level of abstraction. If we move on to open the hard disc and examine its tracks, sectors and read-write heads, we are at the lowest level of abstraction, where no details are invisible.
In the same manner, the database can also be viewed from different levels of abstraction to reveal different levels of details. From a bottom-up manner, we may find that there are three levels of abstraction or views in the database. We discuss them here.
The word schema means arrangement – how we want to arrange things that we have to store. The diagram above shows the three different schemas used in DBMS, seen from different levels of abstraction.
The lowest level, called the Internal or Physical schema, deals with the description of how raw data items (like 1, ABC, KOL, H2 etc.) are stored in the physical storage (Hard Disc, CD, Tape Drive etc.). It also describes the data type of these data items, the size of the items in the storage media, the location (physical address) of the items in the storage device and so on. This schema is useful for database application developers and database administrator.
The middle level is known as the Conceptual or Logical Schema, and deals with the structure of the entire database. Please note that at this level we are not interested with the raw data items anymore, we are interested with the structure of the database. This means we want to know the information about the attributes of each table, the common attributes in different tables that help them to be combined, what kind of data can be input into these attributes, and so on. Conceptual or Logical schema is very useful for database administrators whose responsibility is to maintain the entire database.
The highest level of abstraction is the External or View Schema. This is targeted for the end users. Now, an end user does not need to know everything about the structure of the entire database, rather than the amount of details he/she needs to work with. We may not want the end user to become confused with astounding amount of details by allowing him/her to have a look at the entire database, or we may also not allow this for the purpose of security, where sensitive information must remain hidden from unwanted persons. The database administrator may want to create custom made tables, keeping in mind the specific kind of need for each user. These tables are also known as virtual tables, because they have no separate physical existence. They are crated dynamically for the users at runtime. Say for example, in our sample database we have created earlier, we have a special officer whose responsibility is to keep in touch with the parents of any under aged student living in the hostels. That officer does not need to know every detail except the Roll, Name, Addresss and Age. The database administrator may create a virtual table with only these four attributes, only for the use of this officer.
Summary:
Data and Related Structures
Data are actually stored as bits, or numbers and strings, but it is difficult to work with data at this level.
It is necessary to view data at different levels of abstraction.
Schema:
- Description of data at some level. Each level has its own schema.
We will be concerned with three forms of schemas:
- physical,
- conceptual, and
- external.
Physical Data Level
The physical schema describes details of how data is stored: files, indices, etc. on the random access disk system. It also typically describes the record layout of files and type of files (hash, b-tree, flat).
Early applications worked at this level - explicitly dealt with details. E.g., minimizing physical distances between related data and organizing the data structures within the file (blocked records, linked lists of blocks, etc.)
Problem:
- Routines are hardcoded to deal with physical representation.
- Changes to data structures are difficult to make.
- Application code becomes complex since it must deal with details.
- Rapid implementation of new features very difficult.
Conceptual Data Level
Also referred to as the Logical level
Hides details of the physical level.
- In the relational model, the conceptual schema presents data as a set of tables.
The DBMS maps data access between the conceptual to physical schemas automatically.
- Physical schema can be changed without changing application:
- DBMS must change mapping from conceptual to physical.
- Referred to as physical data independence.
External Data Level
In the relational model, the external schema also presents data as a set of relations. An external schema specifies a view of the data in terms of the conceptual level. It is tailored to the needs of a particular category of users. Portions of stored data should not be seen by some users and begins to implement a level of security and simplifies the view for these users
Examples:
- Students should not see faculty salaries.
- Faculty should not see billing or payment data.
Information that can be derived from stored data might be viewed as if it were stored.
- GPA not stored, calculated when needed.
Applications are written in terms of an external schema. The external view is computed when accessed. It is not stored. Different external schemas can be provided to different categories of users. Translation from external level to conceptual level is done automatically by DBMS at run time. The conceptual schema can be changed without changing application:
- Mapping from external to conceptual must be changed.
- Referred to as conceptual data independence.
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