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What is Data Modelling? : All you need to know [ OverView ]

Last updated on 07th Jan 2023, Artciles, Blog

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Varun Vasanth (ITIL Data Expert )

Varun Vasanth is an ITIL Data Expert with 6+ years of experience and he has expertise in ITSM/ITIL Service Implementations. His articles help to impart knowledge and skills in the core field and get students to acquire informative skills.

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    • In this article you will get
    • What is Data Modeling?
    • Importance of a Data Modeling
    • Advantages of a Data Modelling
    • Data Modeling Terminology
    • Important perspectives of Data Model
    • Types of Data Models
    • Conclusion

What is Data Modeling?

Data Modelling is a process of producing a data model for a data that need to store in the database. A data model highlights an essential data and how must arrange that data. Data models are assure uniformity in the naming conventions, security semantics while an assuring the data quality.

Importance of a Data Modeling

  • A data model assists in a designing the database at a physical, logical, and conceptual levels.
  • The data model establishes a stored procedures, relational tables, foreign and primary keys.
  • It gives a clear picture of a database, and database developers can use it for creating a physical databases.
  • The data model depicts a best understanding of a business requirements.
  • The data model is also useful for an identifying redundant and aslo missing data.
Data Modelling

Advantages of a Data Modelling

  • The data model assists us in identifying proper data sources to be inhabit a model.
  • The Data Model enhances the communication throughout an organization.
  • Data Model assists in a documenting the data mapping in an ETL process.
  • Data modeling enables us to query a data of the database and obtain various reports according to data. Through a reports, data modeling helps in a data analysis.

Data Modeling Terminology

Entity:Entities are an items of the business environment regarding which need to store the data. Example: Customers, Orders, Products, etc.

Attribute:Attributes are give a way of structuring and an organizing the data.

Relationship:Relationship among entities explains how one entity is connected to the another entity.

Reference Table: can resolve the many-to-many relationships among entities into one-to-many and many-to-one relationships through reference table.

Database Logical Design:It explains the database inside data model of a specific database management system.

Logical Design:In a Logical design, create all the keys, tables, rules, constraints, etc.

Database Physical Design:It explains the file organization, internal database storage design and also indexing techniques.

Physical Model:It is a physical depiction of database.

Schema:It is a complete description of a database.

Logical Schema:Logical Schema is the theoretical design of a database that do on a whiteboard or a paper, and it is similar to structural diagram of a house.

Important perspectives of Data Model

1.Logical Model:

The logical model tells how should implement a model. It contains all types of data that we need to capture like a columns, tables, etc. Generally, Data Architects and Business Analysts design a logical data model.

2.Conceptual Model:

It mostly concentrates on a business-oriented attributes, relations and entries. Business Stakeholders, Data Architects design this model.

3.Physical Model:

The physical model specifies how implement a data model through a database management system. It summarizes an implementation methodology with respect to a CRUD operations, tables, partitioning, indexes, etc. Database Developers and Administrators create a Physical Model.

4.Facts and Dimensions:

For learning a data modeling, and must understand a Facts and Dimensions:

Dimension Table:Dimension Table gathers a fields that contain a description of business elements, and various fact tables to refer to it.

Fact Table:Fact Table contains a granularity and measurements of every measurement. Facts may be a semi-additive, additive, For example: Sales.

5.Dimensional Modeling:

Dimensional Modelling is the data designing method of a data warehouse. It utilizes a facts and dimensions and assists in simple navigation. Generally, dimensional models are also known as a star schemas.

Types of Data Models

1.ER (Entity-Relationship) Model:

The ER Model establishes a theoretical view of database. It works around a real-time entities and relationships among them. In a View level, consider aER models as the best option to design a databases.

Entity:

The entity is the real-world object, and and can identify it easily. For instance, in employee database, and consider an employee as an entity. All these entities contain a few properties or attributes that provide them with identity.

Entity Set:

Entity Set is the group of similar types of an entities. Entity sets can have entities in which attributes are share identical values. For instance, an Employee set may have all employees of an organization, similarly, a Student set will have all students of a school.

Attributes:

Represent the entities through properties, and these properties are known as a attributes. Each attribute will have value.

Key:

A Key can be single attribute or a group of attributes that are clearly recognizes an entity in a given entity set. For instance, and can identify an employee among more employees through her/his id.

Relationship:

An Association among entities is known as relationship. For example, a student “studies” in the school. Here “Studies” is a relationship between “Student” and “School” entities.

Relationship Set:

A group of a relationships of a similar type is known as the relationship set. A relationship set will have an attributes, and these attributes are known as a descriptive attributes.

Binary Relationship and Cardinality:

Entities have a four cardinal relationships, they are:

  • One-to-One Relationship
  • One-to-Many Relationship
  • Many-to-One Relationship
  • Many-to-Many Relationship

2.Hierarchical Model

This data model arranges a data in a form of a tree with one root, to which other data is be connected. The tree hierarchy begins with a “Root” data, and extends like a tree, by inserting a child nodes to parent node.In this model, each child node will have only a one parent node.This model effectively explains a several real-time relationships like index of recipes, or a book, etc. The hierarchical model can organizes the data in tree-shape structure with single one-to-many relationship between the two different kinds of data.For example, one college can have a various departments and many faculties.

3.Relational Model

The relational model is most common data model. It arranges a data into the tables, and tables are also known as a relations. Tables will have columns and rows. Each column catalogs an attribute present in an entity like zip code, price, etc.Attributes of relationship are known as domain. can select a specific attribute or a mix of an attributes as the primary key, and and can refer to it in other tables when it is foreign key.Each row is known as a tuple, and it contains a data related to a particular instance of an entity. This Model is also responsible for a relationships among those tables, that comprise one-to-many, many-to-many, and one-to-one relationships.

4.Object-Oriented Database Model

The object-oriented database model explains the database as an object collection, or recyclable software components, with the related methods and features. Following are various types of a Object-oriented databases:

Multimedia Database:A multimedia database includes the media like images that cannot store in relational database.

Hypertext Database:A Hypertext database enables any object to connect to the any other object. It is useful for an arranging plenty of diverse data, yet it is not suitable for a data analysis.An object-oriented database model is a popular post-relational database model, as it includes a tables. This model is also known as hybrid database model.

Network Model:The network model is an extension of a hierarchical model, and it enables a many-to-many relationships among connected records.According to mathematical set theory, construct a network model along with sets of a connected records. Each set comprises a parent record or one owner or at least one child record.A record may be child or member in the multiple sets, by enabling this model and can reveal difficult relationships.

5.Object-Relational Model

The object-relational model is the hybrid database model that blends a some advanced functionalities of object-oriented database model with the ease of relational model.In core, it enables a designers to embed objects into usual table structure.

Data Modelling

Conclusion

Data modeling plays the vital role in storing a data as per user requirement. As users deal with a vast amounts of data, they have to model it for understanding or using it. So, they will use a various types of data models to model a data.

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