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Understanding The Concept Of Data Modeling In Data Science

The concept of Data Modeling can be interpreted as the process of representing data structures in a table for a company’s database which is nothing but building a data model. This data model is a conceptual representation of an association between different data objects.

A Detailed Understanding Of Data Modeling-

The process of Data Modeling occurs in three different layers

  • Physical Model

This is more like a schema that indicates how data is stored physically in the database

  • Conceptual Model

This is simply the user view of the data i.e. the high level which the user sees

  • Logical Model

It sits between the Physical model and conceptual model and it represents the data logically, separate from its physical stores

Why Is The Need For Data Modeling?

Data Modeling helps in presenting a visual representation of data and enforces business logic, regulations, policies, etc on data. It is a guide which is used by scientists and analysts in the designing and implementation of a database. So, without data modelling the job of analysts and scientists to implement the business requirements on database becomes difficult.

Data Modeling ensures the following benefits

  • For accurate representation of data objects for exact results
  • It helps as stated earlier to design database at conceptual, physical and logical levels.
  • Will make easy for the creation of relational tables, primary keys, foreign keys, etc.
  • Database developers can create a better physical database with a good model as it becomes a guiding tool for them

Advantages Of Data Modeling-

There are various advantages are as follow:

  • Helps in better communication of plans across their organization
  • It helps to recognize the correct source of data which can be used to populate the model.
  • This can be used to define relationships between different tables like primary key, foreign key, etc.

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