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It helps plan the database structure before it is built. It is used by database designers to make sure everything is connected
properly.

Dimensional Data Model

This model is used mostly for data analysis and reporting. It is designed to make it easier and faster to read and understand
data (not just store it).
It separates data into:
u Facts: the actual numbers (like sales)
u Dimensions: the details that explain the facts (like date, store, product)
Example:
u Fact: 540 mobiles sold
u Dimensions: sold in Mumbai, in August, by Store Z
This model is often used in data warehouses and business reports, where speed of searching is more important than
saving space.

Benefits of Data Modelling
Data modelling helps to reduce errors in software development. It makes modelling helps different people—like developers,
data experts, and business teams—see and understand how data is connected in a database or data system. It makes
working with data easier and clearer.
Here are some key benefits:

Better Consistency Faster and Smoother
Fewer Mistakes Performance
Everyone follows the
It helps reduce errors same structure and rules, Applications and
while building software or making the system more databases work better and
designing a database. organised. faster when the data is
planned properly.

Easier Data Matching Clear Communication Faster Design Process
It becomes simple to Developers and business It saves time while planning
connect or map data across teams can understand each the database from the
different departments or other better because the basic idea to detailed
systems. model gives a clear picture structure to actual system.
of the data.

Regression

Regression is a Supervised Machine Learning algorithm used to analyse the relationship among dependent variable
(target) and independent variable (predictor). In regression, the variable being predicted is called the dependent variable.
The objective is to determine the most suitable function that characterises the connection between these variables.
It predicts the output values based on input values. It is mainly used for weather forecasting, finding the causal-effect
relationship between variables and time-series modelling.
In regression tasks, there are two kinds of variables being studied: the dependent variables and the independent variables.
u Independent variables: Quantities that can be measured directly.
u Dependent variables: Quantities whose value depends on independent variables.

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