A Model is a core representation of a real object of an application. It is the practice of designing a database using related models. They can be Entity-Relationship model, the Network model, the Hierarchical model and the Relationship model. The reason for data model is: To increase our understanding of business problems, Include the current and add new features as they become necessary for survive in the business commodity, Physical design are a vehicle for capturing and maintaining Meta data like big corporation, banking, finance etc. Modeling a database as a part of the development process can be compared to developing a blue print before constructing a building.

 Modeling tools are evolved from text base tools to graphical oriented PC and Workgroups. Modeling tools makes extensive use of graphical interface and visual editing to produce models. Bachman, Chen, Martin are known as Gurus of data modeling. Each of them has his own methology and notation to model. Most model use Case tool for frequent modeling. A good modeler is like a good reporter asking What, When, How, Where, Why.

 Data models can be physical or logical. Physical data model shows how the data structures are organized so that their resources are optimized. Logical data models interpret the data in the context of the application. A good logical data model is independent of the database management system and can be moved from one management system to another. Databases are concerned with the data entities, their attributes, and the relationships among entities.

 The Physical database is viewed as a data structure. The way information is stored in the physical database depends on the needs of the end user (or customer). The logical design of a database is called Database Schema or simply its Schema. The Conceptual schema is an integrated view of data linking internal and external schemas. The capability to change the internal schema as needed without affecting the external schema is called Data Independence. Schemas are generally written in a data definition language, which generates the schema tables stored in a file called a Data Dictionary. It holds the information about the data.

 A link or bond among two or more entities is called a Relationship. A collection of entities is called an Entity set. The collection of relationship forms a Relationship Set. The relationship model is composed of relations, attributes, domains, keys, and tuple. A relation is a table of rows and columns. Each column of the table is called attribute. The domain of each attribute is the collection of values that can be assigned to a particular attribute. A principal key is one or more attribute values that uniquely identify an entity instance. A tuple is an ordered sequence of elements as in ordered pair. A record is a collection of related fields. Each field contains data items they can be an ASCII character or floating point number, or an array of another records. One of the record fields is set as a key field or index. A file is an abstract data type whose elements are its records.

 In a Relational Database we can form category relationship for relations such as distinguish of entities and identification as One to One, One to Many relationships. Relational data model contains relational operation so that new relations can be formed from existing relations. We can form it by having the principal key attribute of the parent transfer into the entity of the child. The relation then resembles like a Tree Structure.

 The Relational Database Model, which uses relations and relational operations, is most popular version today and is found in many commercial database management systems. A sound database leads to Database Management System (DBMS) that is sharable, reusable, flexible and the accurately reflect the business it supports. Databases need a great deal of memory. They are used extensively in the business world on systems powerful enough to accommodate them.