13 best bi visuals list & chart types explained

BI charts allow people to communicate data and insights to others effectively. The best BI visuals are those that can accurately represent the data and appeal visually to the intended audience. There are many different types of BI visuals, each with its own strengths and weaknesses.

What Is a BI Visual?

A BI visual is a graphical representation of data used to communicate information, or Business Intelligence (BI). These BI charts can be anything from simple bar charts to complex multi-dimensional maps. The best (and most effective) BI visuals can represent the data while capturing and maintaining the reader’s attention.

This article will cover some of the most popular BI visuals and their strengths and weaknesses.

The Best BI Visuals List and Chart Types

  • Bar Charts 
  • Line Charts
  • Pie Charts
  • Doughnut Chart
  • Waterfall Charts
  • Scatter Plots
  • Bubble Charts
  • Area Charts
  • Radar Charts
  • Heat Maps
  • Gantt Charts
  • Treemaps
  • Funnel Chart

Bar Charts

Bar charts are the most straightforward visualizations for data sets that are categorical or nominal in nature. Bar charts can effectively communicate comparisons between different categories at a glance. One can get creative and use stacked or grouped bar BI visuals to communicate data effectively.

Strengths

  • Bar charts can communicate comparisons between different categories effectively.
  • They are easy to understand and interpret.
  • Bar BI visuals are easy to create.

Weaknesses

  • Bar charts can become overcrowded if there are too many categories.
  • They can be confusing if the categories don’t have a logical order.

Line Charts

Line charts work as excellent tools for representing changes over a long period. They work for data sets that are temporal in nature or have a clear trend.

Strengths

  • Line charts are effective at communicating trends over time.
  • These charts are great for attracting new leads looking to achieve long-term gains.
  • Line visuals provide a good amount of space for accurate analysis.

Weaknesses

  • Line charts can be challenging to read when there are too many lines to decipher.
  • They are not visually appealing as other graphs on the list.

Pie Charts

Pie charts work best for data sets that are small in size and have a limited number of categories. They provide a visual representation that focuses on how each category impacts the bigger picture.

Strengths

  • Pie charts are effective at communicating proportions.
  • Summarizing large data sets using text and “pie slices” is easy to interpret.
  • The size of the circle can change to represent the data clearly.

Weaknesses

  • Text can be too small to read when a pie chart has too many categories. 
  • Categories that are very similar in size can be challenging to distinguish from one another.

Doughnut Chart

Doughnut charts are another simple chart structure. The doughnut works the same as the pie chart. They work for groups of all ages and departments because they are visually appealing and have a simple format. 

Strengths

  • They are easy to create.
  • Doughnut charts accurately show proportions.

  • Doughnut graphs are easy for non-professionals to understand.

Weaknesses

  • When you add too many data categories, the text outside the chart can become hard to read.

  • Running out of colors can occur with too many data sets.

Waterfall Charts

Waterfall charts provide a clear path of data. They are great tools for laying out the steps for tasks and goals (and how demanding of resources they may be). Phases in a waterfall chart don’t overlap, giving viewers information that isn’t cluttered or hard to understand.

Strengths

  • Waterfall charts are effective at laying out each step in a process
  • Phases don’t overlap, making it easier to distinguish phases from one another.

Weaknesses

  • Since subtasks are not always defined, it can be hard to discern all of the needs for each task.
  • Making a change to one phase can require changes to other phases, which can become time-consuming.

Scatter Plots

Scatter plots are best for data sets that have only two numerical variables. These graphs are straightforward to create and can immediately show a positive correlation between variables. The simplicity of design gives leaders the ability to focus on solutions instead of needing to explaining the diagram.

Strengths

  • Scatter plots are effective at communicating relationships between non-linear variables.
  • Scatter visuals easily show essential values like the maximum, minimum, and data flow.
  • Creating a scatter plot is simple and doesn’t require lines or bars.

Weaknesses

  • Scatter plots can be hard to read with too many data points.
  • Scatter graphs don’t show the causation of the points, only how they relate to each other numerically.

Bubble Charts

Bubble charts are similar to scatter plots, with the main difference being that bubble charts also encode data using the size of the bubbles. Bubble charts collaborate best with data sets that have three numerical variables.

Strengths

  • Bubble charts are effective at communicating relationships between variables.
  • Summarizing extensive data is easier with the simple design. 
  • Bubble charts can be visually appealing.

Weaknesses

  • Bubble sizes can complicate the overall goal of the chart. 
  • They are not the best visual aid for data sets with more than three variables.

Area Charts

Area charts work for temporal data sets, or those that have a clear trend. Area BI visuals are the most productive way to communicate trends in data. They effectively compare large data sets of different groups. 

Strengths

  • Area charts are effective at communicating trends over time.
  • Area visuals grab the reader’s attention with bright colors.
  • Sizes of different data sets show corresponding relationships.

Weaknesses

  • Area charts can be challenging to read when there are too many data points.
  • In some cases, readers cannot determine the exact values represented.

Radar Charts

Radar charts are superb for data sets with multiple categories with numerical values. They are another option for effectively representing many variables in a way that is visually appealing and less cluttered. The colors overlap in a way that makes it easy to interpret. 

Strengths

  • Radar charts give readers the ability to make comparisons quickly and accurately. 
  • The design of a radar chart is simple, but easily conveys how each category overlaps the other.
  • Radar charts can be visually appealing for presentations.

Weaknesses

  • As with many charts on this list, radar charts can be challenging to read when there are too many data points.
  • The polygon shape of radar BI charts can confuse those unfamiliar with how to read them.

Heat Maps

Heat maps give users a direct view of data sets with two numerical variables. Heat charts work great for understanding how consumers react to products and even websites. Heat visuals will color code values based on behavior.

Strengths

  • Heat maps can effectively convey to business owners how consumers interact with their products and services.
  • Heat charts remove the need to look at numerical data first, exemplifying the differences in each category.

Weaknesses

  • The color dimensions on a heat chart can be limited, so it may not be the best solution for large data sets. 
  • Each group analyzing a heat map can have different conclusions, limiting its accuracy. Heat maps are designed to analyze fixed data from a screenshot. As a result, their scope of analysis is small, and it’s difficult to draw accurate conclusions from constantly-changing data. 

Gantt Charts

Gantt charts are fantastic tools for visualizing goals over time. It identifies relationships between tasks while not appearing overwhelming to the readers. It can help teams and individuals alike stay on top of their goals.

Strengths

  • Gantt charts can be effective at helping teams stay on the path of their goals.
  • Gantt BI visuals can help measure progress over time.

Weaknesses

  • Gantt charts take more effort to create than other chart types.
  • Updating the charts after each milestone or task can be time-consuming.

Treemaps

Treemaps work best for data sets related to sales. They can track data in chronological order. Treemaps can represent all of the data accurately and effectively over time. 

Strengths

  • Tree visuals contain easy-to-read labels.
  • Treemaps can effectively track ROI and sales for items of different categories.
  • These charts can be more straightforward to decipher than pie and donut charts.

Weaknesses

  • As more pixels are added, size distortion can negatively affect the map’s appearance.
  • Treemaps are not the best visual aid for data sets that include negative or zero values.

Funnel Chart

Funnel charts typically help identify problems within a business model as they show the rate of degradation of a particular metric over time. However, they can also work to illustrate chronological steps in a process. Funnel graphs can work similarly to Gantt charts to outline overall business goals.

Strengths

  • Funnel charts can help readers understand the process of reaching company goals.
  • These graphs make it easy to understand what is working in the process and what isn’t by highlighting aspects of the business that are decreasing in performance over a steady time period.
  • The simple shape of the funnel chart can make it easy to understand.

Weaknesses

  • Funnel charts don’t always work well in performing individual analyses.
  • They only focus on conversion or linear goals.
  • If you need to make one change to one part of the funnel, other changes will likely need to follow.

Wrapping Up

Depending on your data and what you want to communicate with your audience, there are many different BI visual chart types to choose from. All 13 of these charts can aid in creating order, analyzing data, and helping the company to succeed at reaching goals.

Related Category Posts:

Boost Your Business With These 12 Data Management Tools
Boost Your Business With These 12 Data Management Tools
Understanding the Need for Data Purity in your Business
Understanding the Need for Data Purity in your Business