---
title: "Overview"
url: https://docs.catalyst.zoho.com/en/quickml/help/data-visualization/overview/
description: "QuickML is a fully no-code ML pipeline builder service in the Catalyst development platform for creating machine-learning pipelines with end-to-end solutions."
last_updated: 2026-08-28T06:26:16Z
service: QuickML
type: general
---

# Data Visualization

## Introduction to Data Visualization:

**Data Visualization** is the graphical representation of data in order to gain insights from 
complex datasets. It plays a crucial role in understanding the data by identifying 
correlations, patterns, and trends, aids in feature engineering, and more. It's very useful 
in building an efficient model. 

**Examples include:**  
- Scatter Plot: Used to visualize the relationship between two variables, such as 
input features and target outputs. They help identify correlations, outliers, and 
data clusters and facilitating feature selection. 
- Heatmap: Employed to evaluate the feature to feature and feature to target 
correlations, anomalies, patterns  visually represented with color grading. 
- Pie chart: Used to show the proportion of each category of a feature in slices 
comprising a whole. 

**Data Visualization charts are segregated into the following four categories:**

<table class="content-table quickml-content-table">
	<thead>
		<tr>
			<th class="w15p">Visualization types</th>
			<th class="w35p">Brief use case </th>
		</tr>
	</thead>
	<tbody>
		<tr>
			<td>Composition charts</td>
			<td>Composition charts show how the parts of the data make up the whole</td>
		</tr>
        <tr>
			<td>Distribution charts</td>
			<td>Distribution charts visually display the distribution or spread of categories in a group.</td>
		</tr>
		<tr>
			<td>Comparison charts</td>
			<td>Comparison charts allow to compare two or more sets of data or variables.</td>
		</tr>
        <tr>
			<td>Relationship charts</td>
			<td>Relationship charts visually illustrate the relationship between two or more variables and how they are correlated with each other.</td>
		</tr>
	</tbody>
</table>