Data Modeling Overview
A Data model is a conceptual representation of data structures(tables) required for a database and is very powerful in expressing and communicating the business requirements.
A data model visually represents the nature of data, business rules governing the data, and how it will be organized in the database. A data model is comprised of two parts logical design and physical design.
Data model helps functional and technical team in designing the database. Functional team normally refers to one or more Business Analysts, Business Managers, Smart Management Experts, End Users etc., and Technical teams refers to one or more programmers, DBAs etc. Data modelers are responsible for designing the data model and they communicate with functional team to get the business requirements and technical teams to implement the database.
The concept of data modeling can be better understood if we compare the development cycle of a data model to the construction of a house. For example Company ABC is planning to build a guest house(database) and it calls the building architect(data modeler) and projects its building requirements (business requirements). Building architect(data modeler) develops the plan (data model) and gives it to company ABC. Finally company ABC calls civil engineers(DBA) to construct the guest house(database).
Advantages and Importance of Data Model
- The goal of a data model is to make sure that all data objects provided by the functional team are completely and accurately represented.
- Data model is detailed enough to be used by the technical team for building the physical database.
- The information contained in the data model will be used to define the significance of business, relational tables, primary and foreign keys, stored procedures, and triggers.
- Data Model can be used to communicate the business within and across businesses.
Data Modeling Development Cycle:
Gathering Business Requirements – First Phase:
Data Modelers have to interact with business analysts to get the functional requirements and with end users to find out the reporting needs.
Conceptual Data Modeling(CDM) – Second Phase:
This data model includes all major entities, relationships and it will not contain much detail about attributes and is often used in the INITIAL PLANNING PHASE.
Logical Data Modeling(LDM) – Third Phase:
This is the actual implementation of a conceptual model in a logical data model. A logical data model is the version of the model that represents all of the business requirements of an organization.
Physical Data Modeling – Fourth Phase:
This is a complete model that includes all required tables, columns, relationship, database properties for the physical implementation of the database.
Database – Fifth Phase:
DBAs instruct the data modeling tool to create SQL code from physical data model. Then the SQL code is executed in server to create databases.