Data Modelling Online courses from Udemy
Data Modelling courses
Data modelling is the process of creating a visual representation of data structures and the relationships between them.
What is Data Modelling?
The purpose of data modelling is to organise data in a way that makes it easier to understand, manage, and analyse.
Data models are used in many different fields and applications, including database design, software engineering, and business intelligence.
In the context of databases, data modelling involves defining the tables, columns, relationships, and constraints that make up a database.
There are several different types of data models, including conceptual, logical, and physical data models.
Conceptual data models provide a high-level overview of the data and the relationships between entities.
Data modeling is typically done using visual tools, such as ER (entity-relationship) diagrams, rather than code. However, here’s an example of a data model in SQL:
CREATE TABLE Customer ( CustomerID INT PRIMARY KEY, FirstName VARCHAR(50), LastName VARCHAR(50), Email VARCHAR(100), Phone VARCHAR(20) ); CREATE TABLE Order ( OrderID INT PRIMARY KEY, CustomerID INT, OrderDate DATE, TotalAmount DECIMAL(10, 2), FOREIGN KEY (CustomerID) REFERENCES Customer(CustomerID) ); CREATE TABLE OrderLine ( OrderLineID INT PRIMARY KEY, OrderID INT, ProductID INT, Quantity INT, Price DECIMAL(10, 2), FOREIGN KEY (OrderID) REFERENCES Order(OrderID) ); CREATE TABLE Product ( ProductID INT PRIMARY KEY, ProductName VARCHAR(50), Description VARCHAR(200), Price DECIMAL(10, 2) );
This example creates four tables in a relational database: “Customer”, “Order”, “OrderLine”, and “Product”.
The tables are related to each other through foreign key constraints. The “Customer” table stores information about customers, including their names, email addresses, and phone numbers.
The “Order” table stores information about orders, including the customer ID, order date, and total amount.
The “OrderLine” table stores information about the items in each order, including the product ID, quantity, and price.
The “Product” table stores information about the products, including their names, descriptions, and prices.
This data model can be used to store and manage data about customers, orders, and products, and to run queries and generate reports based on that data.
Logical data models define the structure of the data in more detail, including the attributes and relationships between entities.
Physical data models define the actual implementation of the database, including the data types, indexes, and storage mechanisms.
Data modelling is an iterative process that involves several steps, including requirements gathering, designing the data model, testing and validation, and implementation.
The goal of data modelling is to create a data model that accurately represents the data and supports the business requirements.
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