Data Modelling

  • Post category:General
  • Post author:

Data modelling (data modelling) is the process of creating a data model for the data to be stored in a database. This data model is a conceptual representation of Data objects, the associations between different data objects, and the rules. Data modelling helps in the visual representation of data and enforces business rules, regulatory compliances, and government policies on the data. Data Models ensure consistency in naming conventions, default values, semantics, security while ensuring quality of the data.

Why use Data Model?

The primary goal of using data model are:

  • 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 data model is labour and time consuming, in the long run, it makes your IT infrastructure upgrade and maintenance cheaper and faster.

Types of Data Models

Types of Data Models: There are mainly three different types of data models: conceptual data models, logical data models, and physical data models, and each one has a specific purpose. The data models are used to represent the data and how it is stored in the database and to set the relationship between data items.

1.Conceptual Data Model: 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 Model: 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 Model: 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.

Conceptual Data Model

Conceptual Data Model is an organized view of database concepts and their relationships. The purpose of creating a conceptual data model is to establish entities, their attributes, and relationships. In this data modelling level, there is hardly any detail available on the actual database structure. Business stakeholders and data architects typically create a conceptual data model.

Logical Data Model

The Logical Data Model is used to define the structure of data elements and to set relationships between them. The logical data model adds further information to the conceptual data model elements. The advantage of using a Logical data model is to provide a foundation to form the base for the Physical model. However, the modelling structure remains generic.

Physical Data Model

Physical Data Model describes a database-specific implementation of the data model. It offers database abstraction and helps generate the schema. This is because of the richness of meta-data offered by a Physical Data Model. The physical data model also helps in visualizing database structure by replicating database column keys, constraints, indexes, triggers, and other RDBMS features.

  • Data modelling is the process of developing data model for the data to be stored in a Database.
  • Data Models ensure consistency in naming conventions, default values, semantics, security while ensuring quality of the data.
  • Data Model structure helps to define the relational tables, primary and foreign keys and stored procedures.
  • There are three types of conceptual, logical, and physical.
  • The main aim of conceptual model is to establish the entities, their attributes, and their relationships.
  • Logical data model defines the structure of the data elements and set the relationships between them.
  • A Physical Data Model describes the database specific implementation of the 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 biggest drawback is that even smaller change made in structure require modification in the entire application.
  • Reading this Data Modelling tutorial, you will learn from the basic concepts such as What is Data Model? Introduction to different types of Data Model, advantages, disadvantages, and data model example.

Shubham Kokane
Data Engineer
Addend Analytics

Addend Analytics is a Microsoft Power BI-partner based in Mumbai, India. Apart from being authorized for Power BI implementations, Addend has successfully executed Power BI projects for 100+ clients across sectors like Financial Services, Banking, Insurance, Retail, Sales, Manufacturing, Real estate, Logistics, and Healthcare in countries like the US, Europe, Switzerland, and Australia. Get a free consultation now by emailing us at kamal.sharma@addendanalytics.com.

Thanks for reading!