In case you didn’t realize, we’re surrounded by big data.
Data science cuts through all of our lives, both online and offline.
For example, data is generated each time you visit a website, shop at a specific store, or watch your favorite show on Netflix.
But how do you analyze this data? Data visualization requires strategy and selecting the most appropriate chart or diagram is part of the process.
In this post, I’ll review different types of data visualizations and help you choose a data analytics style that best fits your needs.
By the way, if you want to visualize your data, check out our Diagram Maker or Chart Maker which let you create beautiful designs in minutes.
Or browse our customizable chart templates or diagram templates to save time and headaches.
Click to jump ahead:
- Bar charts
- Line charts
- Pie chart
- Pyramid chart
- Scatterplots
- Area charts
- Bubble charts
- Flowcharts
- Tree charts
- Gantt charts
- Best practices for data visualization
- Benefits of data visualization
- FAQ
- Conclusion
Bar charts
Also known as bar graphs and column charts, bar charts are popular chart types due to their simplicity.
A bar graph is a type of chart that uses bars to represent and compare different categories of data.
The x-axis on a bar graph represents categories being compared, while the y-axis represents the values or quantities being measured.
Here’s an example:
Why select a bar chart? Well, they make it easy to identify variations in values or disparities between different data points.
So, if you want to communicate the sales or revenue numbers, look no further than bar graphs.
Oh, and they’re incredibly versatile too.
For example, they can be horizontal too like in this example:
Or stacked where a single column is divided into segments that correspond to subcategories like in this example.
Want to learn more about bar charts or see some more examples? Head on over to this post:
Or check out our Bar Graph Maker or bar chart templates to start creating right away.
Line charts
Like bar charts, line graphs or time series plots are another popular graph type, so I’m certain you’ve seen them before.
In a line chart, the x and y axes feature data points connected by lines to visualize progress or changes in data over time.
Here’s an example:
Why use a line chart? Well, they are the perfect tool to describe changes over time such as revenue or variations in employee satisfaction.
In other words, line charts allow businesses to spot trends and patterns and make future forecasts.
And just like bar charts, there’s no shortage of variety.
A multiple line chart can help spot relationships between different variables or categories such as overall cost vs cost per person for an average Thanksgiving dinner like in this example.
Then, there are supply and demand graphs, a special type of line graph that helps predict price changes or analyze market behavior.
Learn more about line charts in this post:
Or check out more examples of line charts you can create by browsing our line chart templates or head straight to our Line Chart Maker.
Pie charts
Besides lines and bar charts, circular pie charts are also a data visualization delight.
Also called circular graphs, pie charts represent the proportion or percentage of different categories within a whole.
Essentially, a pie chart divides a circle into sections, each of which represents a different data point. The size of each sector is proportional to the quantity or percentage it represents, with the total being 100%.
Here are some data visualization examples possible with pie charts:
Pie charts are a great option when you want to display how much each category contributes to the total.
In the real world, this means pie charts are the preferred option to showcase sales and revenue breakdowns or present budget allocation or survey results like in this example.
If you want to add some variety to your pie charts, consider a donut chart.
A donut chart is essentially a pie chart with a hole in the center which can be used to display extra information.
We’ve covered everything there is to know about pie charts in another post. Check it out here:
Or get to creating right away with our Pie Chart Maker and pie chart templates.
Pyramid charts
Pyramid charts are a visualization method used to emphasize relationships and data distribution across categories.
They consist of horizontal bars arranged in the shape of a pyramid.
Each level in a pyramid chart highlights a category and its width or height indicates the size or magnitude.
This shape makes it easy to visualize the distribution of data.
Here’s an example:
Pyramid charts are useful when you want to emphasize relationships between categories or highlight the distribution of data.
Practical applications of pyramid charts include drafting organizational structures or creating educational content like in this example.
Want to learn how to create a stunning pyramid chart? Well, you’re in the right place!
You’ll also find a Family Tree Maker in case you want to go down that route.
Scatterplots
If you want to visualize comparisons between two variables, scatterplots are a natural choice.
A scatterplot consists of individual data points plotted on a coordinate system, with one variable on the x and the other on the y-axis.
Each point in a scatterplot represents a specific observation or data.
Here’s an example:
Scatterplots are a great way to assess relationships between two variables.
By examining the dispersion of data points, you can determine if there is a positive, negative, or no correlation between the variables.
For example, let’s say you’re a new dog owner and want to know what is a healthy weight based on breed.
Well, a scatterplot makes that easy.
And if you really want to add some extra oomph to your scatterplots, you can color-code them as well.
In other words, you can use color to represent a variable to add an extra layer of information.
Here’s an example:
Want more designs? Feel free to browse our scatterplot templates.
Area charts
Area charts often get confused for being a type of line chart, but they’re a separate beast entirely.
Like a line chart, an area chart shows how data changes over time. The x-axis represents the time periods or categories, while the y-axis represents the values or quantities being measured.
However, in area charts, the area between the line and the x-axis is filled in.
Here’s an example:
Area charts are great when you want to showcase cumulative data as the filled areas emphasize total quantity over time or across categories.
The filled area also helps viewers understand the magnitude of data points and compare values.
Area charts are extremely common in finance, sales, and statistics to represent data such as revenue over time or market share.
We’ve got plenty of area chart templates too if you want more options.
Bubble charts
Another powerful tool for data visualization type is bubble charts.
Bubble charts provide a visually appealing way to represent data with three dimensions, making them useful in predictive analytics scenarios.
They are a bit similar to scatterplots in that they display two variables positioned on a coordinate plane.
So what’s different?
Well, bubble charts also utilize different bubble sizes to indicate the magnitude of a third variable.
Here’s an example:
Color can also be used to highlight a fourth variable to add extra layers of information.
Bubble charts are commonly used in finance, economics, and market research, and data analysis.
Here’s a great example of this:
Browse our collection of bubble chart templates for more inspiration.
Flowcharts
Flowcharts are a very popular data visualization option. You’ll see them used in data analytics and cartography to simplify processes and represent workflows in a structured manner.
Flowcharts show the steps, decisions, and connections involved in a clear and structured manner.
A typical flowchart starts with a starting point or an input and ends with a final outcome or output.
Here’s an example of a simple decision flowchart:
The use of various shapes and symbols to represent different steps, decisions, and actions is common as are arrows to indicate the sequence of activities.
Flowcharts are a great choice when you want to analyze complicated processes, pinpoint bottlenecks, optimize a workflow, or make decisions based on a formula.
There are many types of flowcharts to choose from.
The previous example was a decision flowchart, so here’s another example of a process flowchart.
Want to see more flowchart examples and templates you can use? Check out this post!
Or head over to our Flowchart Maker or flowchart templates and pick one you like.
Flowcharts are frequently in software development and project management to document procedures, troubleshoot issues, and communicate processes.
Venn diagrams
No data visualization toolkit is complete without the trusty Venn diagram.
Venn diagrams provide a visual representation of relationships between sets of data or categories.
You’ll often see Venn diagrams used to compare and contrast data, identify unique characteristics, or evaluate overlap between different groups.
I’m sure you recognize their infamous overlapping circles.
But in case you don’t, here’s an example:
I wrote a post explaining the intricacies of Venn diagram symbols to unleash their power. If you want to learn more, I suggest you check it out:
Venn diagrams are great for analyzing intersections or similarities between different data categories.
They are often used in fields such as statistics, probability, market research, and data analysis.
The example above was a two-circle Venn diagram. But of course, you can add more circles if you have more sets of data categories.
Other common types of Venn diagrams include the three-circle and four-circle Venn diagram.
Here’s another example:
Tree charts
Tree diagrams showcase hierarchical relationships and nested subdivisions within a data set.
What does that mean? In simpler terms, a tree diagram breaks down a single category of data into its different parts.
The structure of a tree diagram resembles, well, a tree! The main root is at the top and subsequent levels branch out below.
Here’s an example:
Tree diagrams are frequently used to showcase parent-child relationships, grouping of data, or nested subdivisions.
You’ll recognise them instantly by the nodes and branches that illustrate connections and subdivisions within a system or dataset.
When is a tree diagram actually useful?
If you’re in computer science, organizational management, decision-making processes, and taxonomy classifications.
Another great use for tree diagrams is creating family trees.
I’m sure you’ve seen these everywhere. A family tree diagram is a type of tree diagram that focuses only on lineage and ancestry.
Here’s an example:
Want to learn more about family trees and how you can make your own? Head on over to this post:
You can also utilize a family tree software or start creating beautiful family trees with our Family Tree Maker or tree templates.
Gantt charts
The special honor of the last entry on our list goes to Gantt charts.
A Gantt chart displays a horizontal timeline where each task or activity is represented by a bar.
The length of bars in a Gantt chart corresponds to the duration of the task, and its position on the timeline indicates when the task starts and ends.
Here’s an example:
Gantt charts are invaluable visualization charts for planning, tracking, and managing projects.
They allow managers to visualize the sequence of tasks, identify critical paths, allocate resources, and monitor progress.
What makes Gantt charts particularly effective are the different colors, labels, and symbols to indicate various segments.
Gantt charts are used in various industries, including construction, engineering, software development, and even event planning.
As with other different kinds of charts, we’ve covered how to make Gantt charts and Gantt chart examples extensively in other posts. Check them out here:
- How to Use a Gantt Chart for Project Management [With Examples]
- 11 Gantt Chart Examples For Project Management
Or head straight to creating Gantt charts with our Gantt Chart Maker or Gantt Chart templates.
Best practices for data visualization
Knowing the type of data visualization that best serves your data is just half the battle.
Once you know what type of chart or diagram you’ll be using, you want to spend some time making sure the final output is optimized.
Here’s what you need to do:
- Keep it simple
Avoid cluttering your visualizations with unnecessary elements.
One easy way to do that is just focus on essential data points since simple visualizations are often more effective in conveying information.
- Provide clear labels
Make sure you put clear and concise labels for axes, data points, and other elements.
Labels help your audience understand the context and meaning of the data, making it easier to interpret information being presented.
- Use colors wisely
Utilize colors to highlight key data points and create visual contrast.
Color is a powerful tool to draw attention to important insights or distinguish different categories in data but too much color or contrast can lead to confusion and clutter.
- Provide context
Include explanations to help your audience interpret the data correctly by using titles, captions, and annotations as needed.
Contextual information helps your audience interpret the data correctly.
- Double check your data
Double-check the accuracy of your data to avoid presenting misleading or incorrect information.
What are the benefits of data visualization?
The benefit of data visualization is that it helps businesses identify trends and patterns hidden within raw data.
That might explain the abundance of data visualization tools out there that help you create almost anything from simple graphs to something more complex like flowcharts.
For those looking to delve deeper into this field, exploring the best online data science programs can provide comprehensive education and practical skills necessary for success in this rapidly evolving domain. From analyzing social media trends to optimizing supply chains, its applications are vast and varied.
Here are four ways data visualization is beneficial:
- Leads to better comprehension
Visualizing data makes it easier to understand. Depending on the type of chart you choose, a visual representation of numbers is always a better option.
- Improves data analysis
Patterns, correlations, and outliers that may be missed are more likely to be spotted when data is presented in a visual and interactive format.
- Effective means of communication
Summarizing information in presentations and reports is common practice, but what isn’t common is inserting a 100-row table in a PowerPoint or PDF.
Hence, data visualization is often necessary to communicate in a clear and concise manner.
- Supports decision-making
Charts and diagrams are a great way to evaluate different scenarios, assess risks, and identify opportunities to ensure informed decision-making
Before I share some final words of advice, let’s answer some questions you may have first
Frequently Asked Questions
What are data visualization charts?
Data visualization charts are graphical representations of data that allow us to present complex information in a visually appealing and easily understandable format. These charts provide insights and reveal trends hidden within large datasets. By using different types of data visualization charts, we can facilitate better decision-making based on data.
Are there any free data visualization tools available?
There are several free data visualization tools available online that offer powerful features to create visual representations of data. Among them, Vennage is the best option if you want a user-friendly interface and templates of data visualization charts that serve students, professionals, and data enthusiasts.
What are the different types of data visualization?
Data visualization types vary depending on your goal. However, common visualization types include charts and graphs (bar and line) and diagrams (tree diagram or Gantt chart).
What is the best type of data visualization?
There is no best type of visualization, but rather what format is best for your purpose. For example, to analyze relationships between values, line charts and scatterplots are great. To compare values, a pie chart or bar chart is a better option, and if you want to visualize a process, a diagram like a flowchart is best.
In Summary: Data visualization is a powerful way to understand and communicate complex information
Whether it’s a column graph or a flowchart, each data visualization type serves a unique purpose.
But their end goal remains the same, which is to enable effective analysis and ensure better decision-making.
It doesn’t matter if you’re a student, marketer, or even a scientist, everyone will need some type of data visualization tool at some point, so this list is a great way to understand the different types and pick the best one for you.
And once you’ve decided on a type, don’t forget to sign up for a free Venngage account to create your visualizations.