Data Modeling :
  • Data Modeling is a process of creating a model {prototype} for the data that need to be stored in the database.

  • Data Model is a conceptual representation of the data objects and associations between them.

  • Data Modeling helps to add business logic, rules, etc. to the data objects.

  • Data Modeling is like an architect building plan which helps to build a conceptual model and set the association between data item.

  • Data Model consists of " WHAT " data is needed? " and " HOW " it should be organized? " instead of what operation can be performed on data objects.

Two Types of Data Modeling Techniques:
  1. Entity-Relationship Model  (ER Model)
  2. Unified Modeling Language (UML)



Types of Data Model:
  1. Conceptual Data Model
  2. Logical Data Model
  3. Physical Data Model

1) Conceptual: 
  • This model defines the "WHAT" system contains? , this is generally created by Business Stakeholders or Data Architects.

  • The purpose of this model is to generate Scope, the business concepts of the system.

The main aim of this model is to established the entities, the attributes, and association between them
  •  three basics data models are:

   (a) Entities → a real-world thing.

    (b) Attribute → characteristics and properties of the entity.

    (c) Relationship → dependency and association between two entities.



Figure Description:
  • Here Customer & Product are two entities { table }


  • cust_no, cust_name is the attribute of the Customer entities.


  • prod_name, prod_id is the attribute of the Product entities.

  • sales are the relationship between Customer and Product. 


 2) Logical:
  • This model defines the "HOW" system that will be implemented regardless of the DBMS.

  • The purpose of this model is to generate a technical map and data structure.

  • The logical data model adds further information to the Conceptual Data Model.

  • It defines the structure of the data elements and relationships between them.



3) Physical: 
  • This model defines the " HOW " system that will be implemented using the specific DBMS.

  • The purpose is to implement the actual database.

  • It defines an abstraction of the database and helps to generate the schema.

  • It helps to add RDBMS features. ( like Trigger, Indexes, Constraints, etc.)






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