How to Choose the Right Chart for Data Visualization

In today’s data-driven world, there’s no denying the power of data. However, when data is presented in a cluttered manner, it often loses its impact. The human brain processes visuals 60,000 times faster than text, making visualization an invaluable tool. Clearing up data clutter through visualization tools can bring your data to life, enabling us to truly understand its insights.

 Numerous data experts emphasize decluttering and focus by choosing the appropriate tools for understanding data visualization. With a multitude of visualization tools available, selecting the right way to represent data can be challenging, often hindering the use of advanced data analytics solutions.

 In this blog, we’ll guide you through choosing a data visualization tool that aligns with the role of data in your business.

Starting Your Data Visualization Process

Before selecting a data visualization chart, it’s crucial to understand the purpose of your visualization and ensure proper database management. 

Data is essentially a story conveyed through statistics, and data visualization serves as the visual storytelling of those numbers. Just like any other form of storytelling, you need to identify your audience, grasp the size and nature of your data, and then proceed with the visualization process accordingly. 

To effectively communicate through data visualization, consider how different elements in your data are interrelated. Understanding how data serves your business can aid in selecting the appropriate chart for visualization.

Here are the key ways in which data visualization can be used to depict business performance:

  • Revealing Change
  • Representing a Part of the Whole
  • Facilitating Comparisons
  • Observing Relationships
  • Understanding Data Distribution
  • Leveraging Geographical Data

 By leveraging data in these ways, businesses can choose visualization tools that best serve their data’s purpose. To better understand which tools suit your data visualization message, let’s delve deeper into each motive.

1) Revealing Change

Businesses can use data to illustrate and track changes over time, enabling companies to analyze trends and make informed decisions. These tools typically display various patterns between time and the value being tracked. There are several methods to show differences using data visualization tools:

– Bar Graph:  Suitable for showcasing changes over many years, plotting the variable on the Y-axis against a fixed dimension (usually time) on the X-axis.

– Line Chart: Useful for showing changes over time and comparing trends. Changing elements move horizontally, with upward or downward movement indicating positive or negative changes, respectively.

Box Plot: Depicts the distribution of numeric data using boxes and lines, particularly effective for efficient analysis of data bulk.

2) Representing a Part of the Whole

Businesses often need to highlight specific aspects within a larger context. These tools help understand the significance of one element within a group.

– Pie Chart: Divides a whole circle into parts based on specific elements, with each slice representing a percentage or part of the whole.

– Donut Chart: Similar to a pie chart, but information is displayed in arcs.

– Stacked Bar Chart: Modified bar chart for visualizing how a value varies across multiple categories.

– Stacked Area Chart: Similar to stacked bar charts, ideal for highlighting significant changes in contributions over time.

3) Facilitating Comparisons

Comparison is crucial for uncovering insights. Businesses can identify trends and patterns by comparing essential data with the help of suitable visualization tools.

– Bar Chart: Compares values across sections, using one bar per section. Grouped bar charts can compare variables across multiple sections.

– Line Chart: Compares values between distinct sections using individual lines.

– Dot Plot: Represents values as points on an axis, effective for smaller datasets.

– Box Plots: Compares different data groups, using the box’s shape, average, and spread for comparison.

– Funnel Chart: Displays data in a funnel structure, suitable for showcasing the movement of quantities through a pipeline.

– Bullet Charts: Advanced bar charts that compare two data attributes on a single bar.

4) Observing Relationships

Visualization tools can be beneficial for extracting conclusions from data by establishing relationships between variables.

– Scatter Plot: Represents numeric variables with dots, indicating value and relationships between data points.

– Bubble Chart: Similar to scatter plots, helping understand relationships between multiple categories and trends over time.

– Dual Axis Chart: Presents the relationship between two measures with different scales.

– Heatmap: Detailed and multi-dimensional visualization tool similar to bar graphs.

5) Understanding Data Distribution

Distribution charts showcase the distribution of data/resources across a specific range.

– Bar Charts: Ideal for analyzing progress over time.

– Histogram: Shows the distribution of a single variable across different categories.

– Scatter Plots: Highlights similarities between two datasets.

– Violin Plot: Hybrid of a box plot that combines density and summary information.

– Density Curve: Visually represents the percentage of observations to understand value distribution in a dataset.

6) Leveraging Geographical Data

Geographical data, like longitude and latitude, can be incorporated into data analysis.

– Choropleth: Similar to a heatmap, using color to represent specific data on a thematic map.

– Cartograms: Distort map geometry to display statistics through shades, colors, or dots.


Choosing the right chart for data visualization varies based on the task at hand. The mentioned visualization tools can help you work more efficiently. Aim for simplicity in your visualizations, as the goal is to make data easier to comprehend. 

Whether your data serves a business by revealing change, representing parts of a whole, facilitating comparisons, observing relationships, understanding data distribution, or leveraging geographical data, the objective of data visualization is to enhance readability and understanding. Avoid overwhelming your charts with excessive information.

How We Can Improve Your Data Visualization

As a US-based data visualization consulting company, we offer the following services:

-Tool agnostic Data Visualization Consulting: Visualize unstructured data, transforming it into meaningful insights that enhance your business value using any open source tools like Looker Studio or premium tools like Power BI and Tableau

– Tech Solutions: Provide fully programmed solutions that enable informed decision-making through a serious approach to your data.

If you are looking to start your data visualization process, look no further. Contact Quilytics today.