Data modeling:-

                                Data modeling is the process of creating a visual representation of either a whole information system or parts of it to communicate connections between data points and structures. The goal is to illustrate the types of data used and stored within the system, the relationships among these data types, the ways the data can be grouped and organized and its formats and attributes.

The creation of the data model is the critical first step that must be taken after business requirements for analytics and reporting have been defined. The Data Modeler is a member of the CeDAR staff and will work with the functional users, CeDAR Business Analysts, the BI Solutions Architect and the ETL Developers to create a robust data model.

There are three types of data modeling

1.Conceptual data models

2.Logical data models

3.Physical data models

    1.  Conceptual data model:-

                                                Conceptual data models are the highest level of abstraction. They represent the overall structure of the data and the relationships between different data objects.

   2.Logical data model:-

                                       Logical data models are a step down from conceptual data models. They represent the data in more detail, but they are still independent of any specific database or software application.

  3.Physical data model:-

                                       Physical data models are the lowest level of abstraction. They represent the data in terms of how it is stored in a specific database or software application.

The primary concepts of data models form the foundation of representing and organizing data in a structured manner within a database management system (DBMS). Here are the key concepts: 

1. Entities:-

                Entities represent the real-world objects or concepts that we want to model in the database. They can be people, places, things, or events. Entities have attributes that describe their properties or characteristics. For example, in a customer database, the "Customer" entity may have attributes like name, address, and contact information. 

2. Relationships: -

                           Relationships define the associations and interactions between entities. They represent how entities are related to each other in the database. Relationships can be one-to-one, one-to-many, or many-to-many, depending on the cardinality of the relationship. For example, in a sales database, the "Order" entity may have a one-to-many relationship with the "Product" entity, indicating that an order can consist of multiple products. 

3.. Attributes:-

                      Attributes are the properties or characteristics of entities. They provide additional information about entities and help to describe and distinguish them. Attributes can be singlevalued (having only one value) or multi-valued (having multiple values). For example, the "Employee" entity may have attributes such as employee ID, name, position, and salary.

 4. Keys: -

             Keys uniquely identify each instance of an entity within a database. They ensure data integrity and provide a way to uniquely retrieve and reference data. The primary key is a special key that uniquely identifies each record in a table. It is used to establish relationships between entities and enforce entity integrity.

 5. Constraints:-

                        Constraints define the rules and restrictions that govern the data in a database. They ensure data integrity, consistency, and accuracy. Common types of constraints include entity integrity constraints (e.g., primary key constraint), referential integrity constraints (e.g., foreign key constraint), and domain constraints (e.g., data type constraints, range constraints). 

6. Data Types: -

                       Data types define the format and nature of data that can be stored in attributes. They specify the range of values that an attribute can hold, such as integers, strings, dates, or floating-point numbers. Data types determine how data is stored, manipulated, and validated in the database. 

7. Cardinality:-

                      Cardinality represents the numerical relationship between entities in a relationship. It defines how many instances of an entity can be associated with another entity through a relationship. Cardinality can be one-to-one, one-to-many, many-to-one, or many-to many. 

These primary concepts collectively form the basis of data modeling, which helps in designing and structuring databases to represent real-world information accurately, efficiently, and with data integrity. Data models provide a conceptual framework for understanding and organizing data in a logical and meaningful way within a DBMS