Best Data Visualization Examples to Better Understand Data

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 in raw form. That’s why it’s important to know how to display data in an easy-to-understand visual format. This article will show you some of the best data visualization examples that you can use to inspire yourself as you create your own.

Read on to find out what data visualization is, why it’s so essential, and 10 of the best data visualization examples you can use to help you or others understand the data you’re working with. Whether you’re a data analyst, CEO or in marketing, creating beautiful data visualizations is a fantastic skill to have.

What is data visualization?

Data visualization is the interpretation of raw data sets in a visual format to make the data more digestible. The most common and effective way to visualize data is to take raw data and put it into a graphical representation. We can represent data in many different ways, such as with a bar chart, bubble chart, or donut chart.

There are two main types of data visualization, interactive and static. Static data visualization, which is more primitive, is the use of simple maps and graphs. Interactive data visualization is a new form of graphical representation, which allows us to use a computer or mobile device to modify the data we see in real time. An example of an interactive data visualization is the Manhattan Population Explorer, which allows you to change which parts of Manhattan’s population you can see.

Where is data visualization used?

  • Government
  • Financing
  • Course
  • Service Industries
  • marketing

Why is data visualization important?

Data visualization is important because it helps people read and better understand data. Data is everywhere and most businesses and governments, as well as other industries, use large data sets every day. Raw data is complicated and difficult to understand, but putting it in a graphical representation is a big help.

Data visualization can help people understand patterns in a data set, or it can simply help a researcher who understands the data to explain it to others. These graphics can initiate research and suggest ideas to solve a problem.

Real-life examples of data visualization

We can represent data sets using many different types of models, with numerous chart and chart types to choose from. Below is a list of 10 examples of data visualization that you can use to organize data, make it easy to understand and interpret. This list includes just a few data visualization models, and there are many more to choose from, such as radar charts and column charts.

  1. Line charts
  2. Bar charts
  3. Pie points
  4. heat map
  5. scatter plot
  6. bubble chart
  7. Bullet Chart
  8. box plot
  9. Gantt chart
  10. Waterfall card

10 great examples of data visualization

Data Visualization Example 1: Line Charts

Line charts are a common method of graphical representation of data and are an excellent way to present data in a detailed yet compact manner. Line charts represent data points with dots and straight lines to join these dots. Line charts are also known as line charts and usually represent data with a continuous variable such as money over a period of time.

Data Visualization Example 2: Bar Chart

Bar charts, often referred to as bar charts, are a common type of data visualization and are one of the easiest to learn to create. A bar chart compares related data sets using rectangular bars, which are usually displayed in different colors. It has two axes, X and Yes† The x-axis compares the data sets, while the y-axis represents the value of each category.

Data Visualization Example 3: Pie Chart

Pie charts are pie charts that are similar to bar charts in that they represent and compare related data sets 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 thing, but with a hole in the middle. The downside of a donut chart is that it can be difficult to determine the percentage of each segment.

Data Visualization Example 4: Heat Map

A heat map is a visual representation of the comparison between multiple data sets in the same category. Heat maps show values ​​on a scale, usually from high to low, and show the correlation between two measurements. This example data visualization shows the different data values ​​using variations in color and saturation to demonstrate the difference in values.

Data Visualization Example 5: Scatter Chart

Scatter charts are similar to line charts, but their points represent data points in a chart that are not 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 because it shows the relationship between three variables instead of two. It has an x-axis, a y-axis, and bubbles of different sizes that represent data points. Larger bubbles have a higher value, while smaller bubbles have a lower value. They are a compact data visualization tool best suited for smaller data sets.

Data Visualization Example 7: Bullet Chart

A bullet chart is a type of bar chart that uses horizontal rectangles to display two sets of data, and usually contains more detail than a regular bar chart, which compares a target measure with a primary measure. The target size of the chart is shown with a vertical line, while the primary measure is shown with horizontal rectangles that are compared to qualitative measures displayed in colors in 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 and show the skewness of data. The box-and-whisker plot summarizes a data set into five numbers, including the maximum score, top percentile, median, bottom percentile, and minimum score. These make it easy for researchers to identify mean values ​​by displaying percentiles and means.

Data Visualization Example 9: Combination Chart

Combo charts use features of both bar charts and line charts to display two sets of data with different formats or numerical scales. For example, you can create a combination chart that compares the number of coats sold by a company on a monthly basis to the average monthly temperature on the same visual.

Data Visualization Example 10: Waterfall Chart

A waterfall chart is a visualization model that displays data that has been affected by negative and positive factors over a period of time. It usually shows an analysis of financial rises and falls, with the last value of this chart being the total. Contrasting colors show clear differences between ascents and descents. Some values ​​in these kinds of visualization models do not start from the horizontal axis.

Pro tips to increase your data visualization skills

  • Choose the right visualization model to transfer your data. There are many factors to consider when choosing a data visualization model to display your data. Think about how you want to communicate the data to others, the characteristics of your data and what questions you ask and try to answer.
  • Use the right colors in your data visualization. In data visualization, colors are used to represent equations and related data sets. When comparing two sets of data, you must use more than one color or one color in different shades. The easier each dataset can be distinguished from the others, the easier it will be for others to understand it.
  • Clearly identify the elements of your work. An effective visualization should be easy to read and understand. The best way to do this is to keep the text simple and not clutter the chart or graph you’re working on.
  • Choose a good data visualization tool. There are many easy-to-use data visualization tools that can help you convert your raw data into a useful visual format. Tableau, Infogram, and Plotly are some of the best data visualization programs available on the web today.
  • Get feedback and adjust accordingly. Getting feedback about your work from someone who will use 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 carefully to their feedback and try to implement it in your future work.

What should be the next step in my data visualization learning path?

The next step you can take in your learning journey is to join one of the best data visualization boot camps. Boot camps are an excellent way for people to gain knowledge in a short period of time. Many branches can help you continue learning about data visualization.

Learning and improving your data visualization skills can pave the way for a great job as a data visualization engineer or data visualization analyst. These professionals earn great salaries, with ZipRecruiter reporting that their average annual salary is around $86,990.

Data Visualization FAQ

Which jobs work with data visualization?

Data visualization specialists, data visualization developers, customer service coordinators, marketing specialists, and business intelligence analysts are some of the jobs that work most with data visualization.

What is the best data visualization software?

Qlikview, Tableau, FusionCharts, Highcharts and Plotly are some of the best software for creating static and interactive visualizations. These data visualization tools come at a price, but they make creating a graphical representation of data quick and easy.

What is the highest paying data visualization job?

According to ZipRecruiter, the highest paying data visualization job is a data visualization engineer with an average salary of about $145,551 per year.

Which industries use data visualization the most?

The most prominent industries that use data visualization are the information technology industry, retail and healthcare, and pharmaceuticals. Governments are also major users of data visualization professionals and tools.

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