BISQL – Laymen to SQL Developer # 13 – Database Core Concepts and Applications #1 – Introduction, Data Model, Schemas and Instances
Hi Folks,
This post is part of Series Database Management Systems
Currently running topic for this series is listed as below :
Series of Database Management Systems
>>Chapter 1 : DBMS [Database Management Systems]
>>Chapter 2 : Database Core Concepts and Applications<You are Here>
Continuing from my previous post on this series, If you have missed any link please visit link below
We are going to Cover the Following Points in this article
- Introduction
- Data Model, Schemas and Instances
- The Three-Schema Architecture
Introduction
A database model is a theory or specification describing how a database is structured and used. Several such models like Hierarchical model, Network model, Relational model etc., have been suggested.
Data Model, Schemas and Instances
Data Model |
· It is a set of Concepts for viewing a set of data in a structured way. · This can be easily understood by professionals and non-technical users. · It can explain the way in which the organization uses and manages the information. |
Concepts used in a Data Model |
Entity · An entity is something that has a distinct, separate existence, though it need not be of a material existence. · E.g. – Employee. Attribute · It is the property that describes an entity · It is a characteristic or property of an object, such as weight, size, or color Relationship · Describes the relationship between two or more entities |
Schemas |
· The description of the data base means defining the names, data type, size of a column in a table and database [actual data in the table] itself. · The description of a database is called the database schema [or the Meta data]. · Description of a database is specified during database design and is not frequently changed. Roll No. Name Semester Branch |
Instances |
· The collection of data stored in the database at a particular moment is a database instance or database state or snapshot. · These changes very frequently due to addition, deletion and modification. Roll No. Name Semester Branch 1 Rajesh Prabhu ii E & C |
The Three-Schema Architecture
The Three-schema Architecture has three levels of architecture, an internal level, a Conceptual level and an External level. The three schema architecture is also referred as Client Server Architecture. In this architecture the major advantages lies in that, the division of the architecture into levels allows both developers and users to work on their own levels. They do not need to know the details of the other levels AND they do not have to know anything about changes in the other levels. Note that each of these schemas are only descriptions of data; the data really only exists at the physical level.
1. Internal level
· This is a description of the physical storage structure of the database
· Operations performed here are translated into modifications of the contents and structure of the files
· It has an internal schema.
· It describes the complete details of the stored records and access methods used to achieve efficient access to the data.
2. Conceptual level
· This hides the details of physical storage structures and concentrates on describing entities.
· This level is independent of both software and hardware.
3. External level or view level
· This is outermost layer
· This layer is closest to the users.
· The data viewed by the individual users is called External level.
The Three-Schema Architecture
Data independence:
Data independence is defined as the ability to modify a schema definition in one level without affecting a schema definition in a higher level.
There are two kinds:
1. Physical data independence:
This is the ability to modify the physical scheme without causing application programs to be rewritten. Modifications at this level are usually to improve performance.
2. Logical data independence:
This is the ability to modify the conceptual scheme without causing application programs to be rewritten. This is usually done when the logical structure of database is altered. Logical data independence is harder to achieve, as the application programs are usually heavily dependent on the logical structure of the data. An analogy is made to abstract data types in programming languages.
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