In a world where we are constantly inundated with how to depict data, it is more important than ever to visualize that data in a way that is easy to understand. A data visualization tool can help you make sense of large data sets, spot trends, and make decisions. There are different ways to visualize data and data visualization examples. The right tool for the job depends on the type of data and the question you are trying to answer.
Some common visualization tools include bar charts, line graphs, and scatter plots. With so many choices available, it can be overwhelming to know where to start. This article provides some impressive examples to help you identify the right data visualization tool for your data set.
Table of Contents
What is Data Visualization?
Data visualization turns data into a visual representation, such as a graph or chart. Thereby making it easy for stakeholders and decision-makers to identify trends and make data-driven decisions. Data visualization has applications in various industries, including has applications in various industries, including financial, scientific, and social media.
The best data visualization examples have one thing in common— They make it easier for users to understand the following:
- Pattern: The human brain quickly recognizes patterns. Therefore, visual data can help you identify relationships you wouldn’t be able to see just by looking at raw data. For example, you can use a bar chart to determine the sales performance of different products in different locations.
- Trends: The best data visualizations make it easy to identify trends. For instance, if you look at a sales data graph, you can quickly see whether sales are increasing or decreasing. You can also determine the monthly and yearly sales movement.
- Outliers: Data visualization is a powerful tool for outlier analysis. It can help you to identify unusual patterns and trends, and it can also help you to understand the relationships between different variables in your data set.
What is the importance of Data Visualization?
Data visualization is not just for big businesses. Any company, no matter the size, can use data visualization to improve its bottom line. B2B businesses can use visualizations to make content, and messaging can use visualizations to make content and messaging more engaging and informative. By incorporating charts and graphs into their posts, bloggers can communicate complex ideas more effectively and connect with their readers on a deeper level.
Some general importance of data visualization include:
Easy to Understand
let’s face it, large data sets are often difficult to understand. However, you can easily understand the most complex data sets with data visualization. For example, you can easily represent areas hugely affected by the Covid-19 pandemic using a heat map.
Let’s face it, large data sets are often difficult to understand. However, you can easily understand the most complex data sets with data visualization. For example, you can easily represent areas hugely affected by the Covid-19 pandemic using a heat map.
Spot Patterns
As mentioned earlier, charts and graphs make it easy to spot patterns and identify trends. As mentioned earlier, charts and graphs make it easy to spot patterns and identify trends. This can be extremely helpful in various fields, from spotting trends in the stock market to identifying early warning signs of disease. Identifying patterns can also inform marketing strategies and inform marketing strategies and predictions.
Storytelling Is More Engaging
At a time when human attention is thinly spread across so many things, it’s more important than ever to communicate effectively and efficiently. That’s where data visualization comes in. Data visualization is especially well suited to storytelling. A good story can help you make sense of complex data, remember key points, and empathize with the characters involved.
Improve Speed In Decision Making Process
Data visualization is a valuable tool for businesses. It improves the speed of decision-making by allowing managers to spot patterns and data trends quickly. Interactive data visualization can also help businesses identify opportunities and optimize their operations.
What are Common Forms of Data Visualization?
There are different types of data visualization, some of which include:
- Bar graphs: A bar graph is a representation of data using rectangular bars to compare values. The lengths of the bars represent the magnitude of the data. You can use bar graphs to show the relationships between data groups or categories.
- Column charts: A column chart is a graph that shows data using vertical bars. It is often used to compare data among different groups. Column charts are easy to read and understand, making them popular for data visualizations.
- Area charts: An area chart is a two-dimensional graph that uses line segments to connect data points and show areas of the plane that are enclosed by those line segments. The segments can be of any length but are often horizontal or vertical.
- Dual-axis charts: A dual-axis chart is a line graph that uses two independent axes to display data. Dual-axis charts can be used to compare two variables or to show how one variable changes about another.
- Line graphs: A line graph is a data visualization graph that shows how something changes over time. It is made up of a series of points connected by lines. Line graphs can represent changes in weather, population, or sales.
- Pie charts: A pie chart is a circular statistical graphic divided into sectors to illustrate numerical proportions. In a pie chart, the arc length of each sector corresponds to the quantity it represents. Pie charts are popular for showing the proportions of a whole.
- Heatmaps: A heatmap is a graphical representation of data where the individual values contained in a matrix are represented as colors.
- Scatter plot chart: A scatter plot chart, also known as a scatter diagram or a scattergraph, is a type of plot or mathematical diagram using cartesian coordinates to display values for typically two variables for a data set.
What Makes A Great Data Visualization?
Comprehensibility and applicability are two characteristics that are essential for every data visualization tool. However, that is not sufficient.
According to Ben Shneiderman, “The purpose of visualization is insight, not pictures.” Great data visualizations effectively convey the data it represents. This can involve using the right chart type, colors, labels, and legends. Generally, a great data visualization should be easy to understand and interpret.
What are the Principles of Great Data visualizations?
When it comes to data visualization, there are certain principles that you need to follow to create a compelling and impactful visual. Follow the following principles to enhance the look of your data presented:
Defining a Clear Purpose
Data visualization requires a defined goal. This way, you can quickly identify the right data visualization tool for your project. For example, a line chart would be a good choice for spotting trends and outliers. A bar chart would be more appropriate if you want to compare two different data groups.
Know About Audience
The audience is one of the most important aspects when creating interactive data visualizations. It is essential to consider who will view the visualizations of data and their needs.
Remark: Tips for data visualization
What are the Best And Most Effective Examples of Visualizing Data?
Take a look at some of the most impressive instances of data visualization over the last several years:
Bubble Chart Visualization
An impressive bubble chart visualization example is the Sales analysis of shoes of different brands for Harry’s SuperMart for a month. An impressive bubble chart visualization example is the Sales analysis of shoes of different brands for Harry’s SuperMart for a month.
Best Scatter Plot
The chart below displays the effect of temperature on beer and ice cream sales revenue.
Best Distribution Chart
A box and whisker chart is a great tool for visualizing distributions. An impressive example is the chart below showing US annual retail industry sales distribution.
Radar Chart Visualization
Radar charts have applications in business performance, quality analysis, and product comparison. An example is comparing the results of a customer feedback survey based on five categories.
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Line Charts Visualization
Line charts may be useful in various contexts, including the analysis of product comparisons, corporate performance, and event and historical data. A typical example can be seen in the chart below, comparing the number of visitors during the week.
Bar Graph Visualization
In the example below, the bar graph displays the relationship between the number of wins and matches played for each major league baseball team.
What is the Best Tool for Data Visualization?
When we pick the best tool for data visualization, there are a few points to think about:
- Support a wide range of data visualization methods
- Ease of use
- Pricing
- Customer support
- Customization
- Data security
- Ability to share data outside of the tool
Considering all these factors, FusionCharts is the best Data Visualization tool. FusionCharts is the best data visualization library to create beautiful web and mobile dashboards with our interactive and responsive charts, extensive documentation, consistent API, and cross-browser support. Your next great dashboard starts here!
Conclusion
Data visualization is a process of representing data in a visual format. It is an effective way to communicate information to your audience. The right data visualization tool gives you limitless customization control to suit your specific needs. When used correctly, stakeholders and decision-makers can make faster, more informed, data-driven decisions that ultimately boost the bottom line.
Looking to add visualizations to your project? FusionCharts, a javascript charting library with 100+ charts, can help you get started.
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