In this modern age, all industries rely heavily on the interpretation of digital data, the amount of which is also increasing day by day. This data can be challenging to understand when it is in its raw form, which is why knowing how to display data in an easily comprehensible visual format is important. This article will show you some of the best data visualization examples you can use to inspire yourself when trying to create your own.
Continue reading to find out what data visualization is, why it is so essential, and 10 of the best examples of data visualization you can use to help you or others understand the data you are working with. Whether you’re a data analyst, a CEO, or working in marketing, creating beautiful data visualizations is a fantastic skill to have.
What Is Data Visualization?
Data visualization is the interpretation of raw datasets into a visual format to make the data more digestible. The most common and effective way to visualize data is by taking raw data and putting it into a graphical representation. We can display data in many different ways, such as using a bar chart, bubble chart, or donut chart.
There are two major kinds of data visualization, interactive and static. Static data visualization, which is more primitive, is the use of simple maps and charts. Interactive data visualization is a new form of graphical representation, allowing us to use a computer or mobile device to change the data that we see in real time. An example of an interactive data visualization is the Manhattan Population Explorer, which lets you modify which parts of Manhattan’s population you can see.
Where Is Data Visualization Used?
- Service Industries
Why Is Data Visualization Important?
Data visualization is important because it helps people read data and understand it better. Data is everywhere, and most businesses and governments, as well as other industries, use large datasets every day. Raw data is complicated and difficult to understand, but putting it into graphical representation helps a lot.
Data visualization can help people understand patterns in a dataset, or it can simply help a researcher who understands the data explain it to others. These graphical representations can initiate research and propose ideas to solve a problem.
Real-World Examples of Data Visualization
We can represent datasets using many different kinds of models, with numerous graph and chart types to choose from. Below is a list of 10 data visualization examples that you can use to organize data and make it easy to understand and interpret. This list includes only a few data visualization models, with many more to choose from, such as radar charts and column charts.
- Line Charts
- Bar Charts
- Pie Charts
- Heat Map
- Scatter Plot
- Bubble Chart
- Bullet Graph
- Box Plot
- Gantt Chart
- Waterfall Chart
10 Great Examples of Data Visualization
Data Visualization Example 1: Line Charts
Line charts are a prevalent method of graphical representation of data and are an excellent way to show data in a detailed but compact way. Line charts represent data points using dots and straight lines to join these dots. Line charts are also known as line graphs and usually represent data with a continuous variable such as money over a defined period of time.
Data Visualization Example 2: Bar Chart
Bar charts, which are often referred to as bar graphs, are a common type of data visualization and are one of the easiest to learn to make. A bar chart compares related datasets using rectangular bars, usually shown in different colors. It has two axes, x and y. The x-axis compares the datasets while the y-axis represents each category’s value.
Data Visualization Example 3: Pie Chart
Pie charts are circular charts similar to bar graphs as they represent and compare related datasets and usually do so in the form of percentiles or fractions. Pie charts are also often referred to as donut charts, which are essentially the same but with a hole cut out in the middle. The disadvantage of a donut chart is that it can be hard to determine the percentage of each segment.
Data Visualization Example 4: Heat Map
A heat map is a visual presentation of the comparison between multiple datasets in the same category. Heat maps show values on a scale, usually from high to low, and display the correlation between two measures. This data visualization example shows the different data values using variances in color and saturation to demonstrate the difference in values.
Data Visualization Example 5: Scatter Chart
Scatter charts are similar to line graphs, but their dots represent data points on a graph that aren’t connected by a line. A scatter chart shows the correlation between two variables and is a compact data visualization model that displays a lot of data in one place. It is a classic data visualization method and is an excellent way to find outliers in a dataset and understand the distribution.
Data Visualization Example 6: Bubble Chart
A bubble chart is very different from the other data visualization models we’ve mentioned so far, as it shows the relationship between three variables rather than two. It has an x-axis, a y-axis, and different-sized bubbles representing data points. Bigger bubbles have a higher value, while smaller bubbles have a lower value. They are a compact data visualization tool best suited for smaller datasets.
Data Visualization Example 7: Bullet Graph
A bullet graph is a kind of bar graph that uses horizontal rectangles to display two datasets, and usually includes more details than a regular bar graph, comparing a target measure with a primary measure. The target measure of the chart is shown with a vertical line while the primary measure is displayed with horizontal rectangles which are compared to qualitative measurement shown in colors on the background.
Data Visualization Example 8: Box Plot
Box plots, also known as box-and-whisker plots, are a visual representation of the distribution of numerical data, showing the skewness of data. The box-and-whisker plot summarizes a dataset into five numbers, including the maximum score, upper percentile, median, lower percentile, and minimum score. These make it easy for researchers to identify mean values by displaying percentiles and averages.
Data Visualization Example 9: Combination Chart
Combination charts use features from both bar graphs and line charts to represent two datasets with different formats or numeric scales. For example, you could make a combination chart that compares the number of jackets sold by a company on a monthly basis along with the average monthly temperature on the same visual representation.
Data Visualization Example 10: Waterfall Chart
A waterfall chart is a visualization model that displays data affected by negative and positive factors over a certain period of time. It usually shows an analysis of financial increases and decreases, with the last value of this graph being the total. Contrasting colors show clear differences between increases and decreases. Some values in this kind of visualization model do not start from the horizontal axis.
Pro Tips to Boost Your Data Visualization Skills
- Pick the right visualization model to convey your data. There are many factors to consider when choosing a data visualization model to display your data. Consider how you would like to communicate the data to others, your data’s characteristics, and which questions you are asking and trying to answer.
- Use appropriate colors in your data visualization. Colors are used in data visualization to show comparisons and related datasets. When comparing two sets of data, you should use more than one color or one color in different shades. The more easily each dataset can be discerned from the other, the easier it’ll be for others to understand.
- Label the elements of your work clearly. An effective visualization should be simple to read and understand. The best way you can do this is by keeping the text simple and not cluttering the chart or graph you are working on.
- Choose a good data visualization tool. There are many easy-to-use data visualization tools that can assist you with transforming your raw data into a helpful visual format. Tableau, Infogram, and Plotly are some of the top data visualization programs available on the Internet right now.
- Get feedback and adjust accordingly. Asking for feedback on your work from someone who will be using it can improve your data visualization skills and help you keep learning. Their feedback will help you make your visualization easier to read and understand. Listen to their feedback carefully and try implementing it in your future work.
What Should Be the Next Step in My Data Visualization Learning Journey?
The next step you can take in your learning journey is by attending one of the best bootcamps for data visualization. Bootcamps are an excellent way for people to gain knowledge in a short amount of time. Many establishments can help you continue learning data visualization.
Learning and improving your data visualization skills can open up pathways to a great job as a data visualization engineer or a data visualization analyst. These professionals earn great salaries, with ZipRecruiter reporting their average yearly salary to be around $86,990.
Data Visualization Examples FAQ
Data visualization specialists, data visualization developers, client services coordinators, marketing specialists, and business intelligence analysts are some of the jobs that work most commonly with data visualization.
Qlikview, Tableau, FusionCharts, Highcharts, and Plotly are some of the best software for making static and interactive visualizations. These data visualization tools do come at a price, but they make creating a graphical representation of data quick and simple.
According to ZipRecruiter, the highest-paying data visualization job is a data visualization engineer which has an average salary of around $145,551 per year.
The most prominent industries that use data visualization are the information technology industry, retail industry, and the healthcare and pharmaceutical industry. Governments are also big users of data visualization professionals and tools.
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