Data Modeling Concepts

Data modeling is the process of documenting a complex software system design as an easily understood diagram, using text and symbols to represent the way data needs to flow. The diagram can be used as a blueprint for the construction of new software or for re-engineering a legacy application. A data model visually represents the nature if data, business rules governing the data, and how it will be organized.

Types of Data models :

There are mainly three types of data models :

1. Conceptual data models : This Data Model defines WHAT the system contains. This model is typically created by Business stakeholders and Data Architects. The purpose is to organize, scope and define business concepts and rules.

2. Logical data models :  Defines HOW the system should be implemented regardless of the DBMS. This model is typically created by Data Architects and Business Analysts. The purpose is to developed technical map of rules and data structures.

3. Physical data models :  This Data Model describes HOW the system will be implemented using a specific DBMS system. This model is typically created by DBA and developers. The purpose is actual implementation of the database.

We can understand the data modeling process by the diagram below :


Traditionally, data models have been built during the analysis and design phases of a project to ensure that the requirements for a new application are fully understood. A data model can be thought of as a flowchart that illustrates the relationships between data. 

Advantages of Data model :

  • The main goal of a designing data model is to make certain that data objects offered by the functional team are represented accurately.
  • The data model should be detailed enough to be used for building the physical database.
  • The information in the data model can be used for defining the relationship between tables, primary and foreign keys, and stored procedures.
  • Data Model helps business to communicate the within and across organizations.
  • Data model helps to documents data mappings in ETL process
  • It helps to recognize correct sources of data to populate the model.

Disadvantages of Data model :

  • To developer Data model one should know physical data stored characteristics.
  • This is a navigational system produces complex application development, management. Thus, it requires a knowledge of the biographical truth.
  • Even smaller change made in structure require modification in the entire application.



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