5 Most Common Data Visualization Types and When to Use Them

Last Updated: April 6, 2021

We live in a data-driven world, where every single one of us operates with data, charts, and reports on a day-to-day basis. But data mean little on its own unless visualized in the form of useful information. Data visualization renders raw data in the form of graphical diagrams and reports, yielding actionable information.

Choosing the right visualization can be tricky. Building an insightful and powerful report that accelerates decision making lies in the understanding of your business needs. Here is a complete guide for the most commonly used types of data visualization and when to choose what. 

Visualizing data is crucial to ensure that all the data you collect translates into decisions that amplify your business growth. Here are five data visualizations that are commonly used by companies across the world.

1. Bar Chart

Bar charts or column charts have rectangle bars arranged on the X or Y-axis. Comparing objects by aligning them with the same parameters is the most popular visualization out there. Bar charts can be used to track changes over time. However, bar graphs used for time series yield accurate results when the changes are considerably large. There are different categories of bar graphs like stacked bar graphs, 100% stacked bar graphs, grouped bar graphs, box plots, and waterfall charts (advanced bar graphs).

Bar charts are most suitable for:

  • Comparing a numerical value across categories
  • Identifying the order within a category
  • Representing a histogram (where the values on the X-axis are grouped into buckets)

Use Case: You can use a bar chart for a visual representation of your overall business revenue against your peers. If you want to compare the individual split of product-wise revenue, your best choice would be a stacked/grouped bar chart.

Bar chart

2. Doughnut Chart or Pie Chart

A Doughnut chart slices a doughnut into multiple parts based on the field value. Doughnut charts or pie charts are suitable to depict parts of a whole relationship, where all units together represent 100%. Drilled-down doughnut charts are interactive and help users decipher complex data to get to the source of the issue or the solution.

Use Case: You can analyze your budget using a doughnut chart. Splitting the total budget across your expenses, investments, loan, savings, etc. would give you an instant understanding of your budget plan.

Doughnut chart

3. Line Graph or Line Chart

Line graphs have values plotted as lines across the X and Y-axis. They are used to track changes over a short/long time frame. Line graphs are better to use than bar graphs particularly when the changes are minor. You also have the multi-line graph option when you need to compare changes over the same time period for more than one attribute.

Line graphs are best used to:

  • Display trend over a time series
  • Pinpoint outliers
  • Visualize forecasted data

Use Case: Say, you want to analyze your business’ month-wise expenditure. The line graph will give you the best rendition by plotting the values across months on the X-axis and expenditure on the Y-axis.

Line chart

4. Pivot Table

Pivot table as the name indicates has columns and rows with aggregated values populated in the cells. The pivot table is the most straight-forward visualization that can be used to convey a huge amount of data at a single glance. It is easy to build and flexible to modify. However, unlike the other infographic visualizations discussed here, tables are not graphical and hence can be used only in specific cases —

  • When you want to compare different unrelated metrics required
  • When there are relatively lesser rows (display of data at the top level as opposed to the granular level)

Use Case: Financial reports are generally depicted over tables. Bringing in the years on rows and operating cash flow, investing cash flow, cash from financing, and other metrics on the columns will help you understand your business’s cash flow over the years.

Pivot table

5. Scatter Plot

Scatter plot shows the relationship of the common attribute between two numerical variables plotted along both X and Y axes. If you are a data scientist working with different sets of data, scatter plot would be something that you commonly work with, but for a novice user, it could be a little unfamiliar. Scatter plots are best suitable to compare two numerical values simultaneously. Segmentation charts and bubble charts are the advanced versions of the scatter plot. The segmentation chart demarcates the scatter plot into four quadrants, making the choice of the users easier. Bubble sort brings in an additional dimension to the chart by displaying varied sizes of bubbles over the scatter plot. 

Use Case: You can present data for product price revision using the scatter plot by bringing in the number of units sold on the X-axis, current price on the Y-axis, and the products on the quadrant. It will give you a clear outlook on the products that have a low price yet have sold a good deal and can be considered for price increment. Alternatively, you can bring in a price drop for products that have a high price but are in low demand.

Scatter plot

These types of charts, along with area charts, heat maps, and treemaps are widely used visualization techniques by data analysts, marketers, and financial analysts across the world. However, there are specific visualizations that can be used to tackle the reporting needs of unique data sets – for instance, it would be ideal to use choropleth (Map chart), tree diagram, and radar chart for geospatial, conditional, and multivariable data points respectively. Choosing the perfect visualization from different types of data visualizations can be challenging, but with a basic understanding of these fundamental charts, your choice will be easier.

Reporting and Data Visualization with HappyFox BI

“There is no such thing as information overload. There is only bad design.” – Edward Tufte

HappyFox BI is a coherent, robust BI tool that offers a huge list of visualizations for you to choose from. Visualization types within the tool range from simple visualizations like the ones discussed above to advanced, niche visualizations like Pareto, segmentation, and Gantt charts. HappyFox BI also comes with a huge set of pre-built templates suitable for numerous use-cases that can be instantly used to construct your report.

Get a demo today to leverage analytics with HappyFox BI and explore the functionalities and various data visualization tools it has in store for you.