Data Modeling

What is data modeling?

• A data model refers to the logical inter-relationships and data flow between different data elements involved in the information world.
• It also documents the way data is stored and retrieved.
• Data models help represent what data is required and what format is to be used for different business processes.

There are two data modeling techniques

• Entity-Relationship (E-R) Model
• UML (Unified Modelling Language)

Why use data modeling?

• Ensures that all data objects required by the database are accurately represented. Omission of data will lead to creation of faulty reports and produce incorrect results.
• A data model helps design the database at the conceptual, physical and logical levels.
• Data Model structure helps to define the relational tables, primary and foreign keys and stored procedures.
• It provides a clear picture of the base data and can be used by database developers to create a physical database.
• It is also helpful to identify missing and redundant data.
• Though the initial creation of the data model is labor-intensive and time-consuming, in the long run, it makes your IT infrastructure upgraded and maintenance cheaper and faster.

Types of data models

Conceptual

• The main aim of this model is to establish the entities, their attributes, and their relationships. In this Data modeling level, there is hardly any detail available of the actual Database structure.

Logical

• Logical data models add further information to the conceptual model elements. It defines the structure of the data elements and set the relationships between them.

Physical

• A Physical Data Model describes the database-specific implementation of the data model. It offers an abstraction of the database and helps generate the schema. This is because of the richness of meta-data offered by a Physical Data Model.

Source: https://www.guru99.com/data-modelling-conceptual-logical.html