Have you ever tried to present an exciting idea or a business insight obtained from data analysis to an audience filled with stakeholders, business holders and generally individuals who don't exactly speak ‘numbers' and have been met with blank stares? According to the University of Minnesota, your brain processes visuals 60,000 times faster than textual information.1
This implies that with charts, graphs or a well presented infographic, the data that once seemed complex is simplified. Data visualization can help you communicate what seemed like complex data sets to your audience. Additionally, you can gain valuable insights that allow you to make informed decisions much quicker! Hence, increasing overall efficiency of a company.
In this article, we will explore the different types of data visualization, the various visualization tools and software available, and how to choose the right chart or graph for your data. We will also discuss the benefits of data visualization and how it can be used to gain valuable insights.
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How Many Types Of Data Visualization Are There?
Data visualization is a powerful tool for understanding data, uncovering patterns, and making informed decisions. It can be used to explore and analyze data in a variety of ways, from simple charts and graphs to complex interactive maps and infographics.
The most challenging aspect of having so many visualization options is deciding which one is best for your data. Your decision ultimately depends on the type of data you are working with and the story you are trying to tell. With the right visualization tools and software, you can create stunning visuals that will help you gain insights and make informed decisions.
So, how many types of data visualization are there? Generally, there are three main categories of data visualization: charts, maps, and infographics. Each of these categories can be broken down into more specific types of visualizations, such as bar charts, line charts, geographic maps, heat maps, flow maps, dot maps, storytelling infographics, comparison infographics, hierarchical infographics, and geospatial infographics.
Types Of Data Visualization
There are many different types of data visualization, each with its own advantages and disadvantages. Here are some of the most common types of data visualization:
Charts are a popular way to visualize data, as they allow users to quickly and easily compare different values. There are several types of charts each having its unique properties to perform a needed function.
- Bar Chart: Bar charts are used to compare different values across categories. They are especially useful for comparing values over time, as each bar represents a single data point. Bar charts can be horizontal or vertical, depending on the data being presented.
- Line Chart: Line charts are used to show the relationship between two variables. They are often used to show trends over time. Each data point is connected with a line, allowing users to see how one variable changes as the other changes.
- Pie Chart: Pie charts are used to compare the relative sizes of different parts of a whole. Each part is represented by a “slice” of the pie, with the size of the slice indicating its relative size.
- Gantt Chart: Gantt charts are used to track the progress of a project over time. Each task is represented by a bar, with the length of the bar indicating the amount of time required to complete the task. Gantt charts are especially useful for tracking the progress of complex projects.
Maps are one of the most powerful tools for data visualization. They allow us to visualize geographical data, such as population density, weather patterns, and political boundaries, in an easy-to-understand format.
The most popular types of maps are:
- Geographic Maps: These are the most common types of maps used for data visualization. They are used to show the location of a place on a map. They can also be used to represent the physical features of a region, such as rivers, roads, and cities. Other uses of geographic maps include the illustration of population density, income levels, and land use patterns.
- Heat Maps: Heat maps are used to show the intensity of a phenomenon over a geographic area.If you want to determine the intensity of a disease, distribution of a population or even temperature over a specified location, then heat maps will provide the visuals you need. They are created by assigning colors to data points, with the darkest colors representing the highest intensity.
- Flow Maps: Flow maps are essentially used to show the ‘flow’ of people or goods from one place to another. They are commonly used to visualize population migrations, the movement of goods and services, or the spread of disease. Flow maps are created by drawing arrows between two points to represent the movement of a particular item.
- Dot Maps: Dot Maps are used to represent the geographical distribution of data points. They are created by placing dots on a map to represent the location of each data point. Dot maps are an effective way to quickly identify clusters of data points and can be used to visualize a variety of data, such as population density or crime rates.
Simply put, infographics are used to visually represent complex data in an easy-to-understand format. They are an interesting form of data visualization as they employ the use of captivating visuals to communicate information in a clear and engaging manner. The most popular types of infographics are storytelling, comparison, hierarchical, and geospatial.
- Storytelling: Storytelling infographics are used to accomplish just what the name promises, tell a story! They focus on telling a story, rather than just presenting data. These types of infographics often use illustrations, icons, and text to explain the data in an engaging way. They can also explain a process or provide an overview of a situation.
- Comparison: Comparison infographics are used to compare two or more sets of data. They are designed to show how two or more variables relate to each other and can be used to illustrate trends or correlations. These types of infographics often use bar charts, line graphs, or other types of charts to compare the data.
- Hierarchical: Hierarchical infographics are used to show the relationship between different data points. They often use a tree-like structure to show the hierarchy of data, with the most important information at the top and the least important information at the bottom.
- Geospatial: Geospatial infographics are used to show data in relation to geographic locations. They use maps to show the locations of data points or to illustrate trends in different areas. They can also be used to show the spread of disease, population density, or other geographic information.
Visualization Tools And Software
To create visuals to present data, you must have the right tools and software and depending on the type of data visualization you want to create, there are a variety of tools and software available to choose from.These tools and software range from simple to complex and can be used to create a variety of visualizations. Some of the most popular tools and software include Tableau, Microsoft Power BI, and Google Charts.
Tableau: This is a powerful data visualization tool that allows users to quickly and easily create interactive visualizations. It offers a wide range of features such as drag-and-drop functionality, data blending, and real-time analytics. It also offers a variety of charts, maps, and graphs to choose from.
Microsoft Power BI: This tool is a cloud-based business intelligence platform that enables users to create interactive visualizations from a variety of data sources. It offers features such as natural language query, data mash-up, and predictive analytics. It also offers a range of charts, graphs, and maps to choose from.
Google Charts: This is a free web-based tool that allows users to create interactive data visualizations. It offers a wide range of charts, graphs, and maps to choose from and also allows users to customize the look and feel of their visualizations.
How To Choose The Right Chart Or Graph For Your Data
Choosing the right chart or graph for your data is a crucial step in creating an effective data visualization. The wrong chart or graph can lead to misinterpretations or confusion, while the right one can make complex data easier to understand and draw meaningful insights from.
When choosing the right chart or graph for your data, you should consider the following steps:
Step 1: The Type Of Data
The type of data you are working with is an important factor that will greatly inform the type of visualization required. Different types of data require different types of visualizations.
For example, categorical data such as gender or age are best presented with bar charts, while numerical data such as sales or temperature are better suited to line graphs.
Step 2 : The Goal Of The Visualization
Another factor to consider is the goal of visualization. Different types of graphs and charts can be used to answer different questions. For example, a bar chart can be used to compare different categories, while a line chart can be used to track changes over time.
Therefore, the end goal will determine the type of visualization needed.
Step 3: The Audience
Finally, the audience is another important factor to consider. . Different types of charts and graphs can be more or less understandable to different audiences. For example, a pie chart may be easier to understand for a general audience, while a scatter plot may be better suited for a more technical audience.
It is important that all these points are taken into consideration. With the right chart or graph, data can be presented in a way that is easy to understand and can lead to meaningful insights.
Feel free to read here for more information on how to make use of your business data with visualization tools .
Benefits Of Data Visualization
Data Visualization is an invaluable tool for understanding complex data. By transforming large datasets into easy-to-understand visuals, it helps uncover trends, patterns, and relationships that would otherwise be hidden. It also enables us to make informed decisions quickly and easily.
The main benefits of data visualization include:
Improved Understanding: Data visualization helps to make sense of large datasets by transforming them into visuals that can be easily comprehended. This helps to identify patterns, trends, and correlations that would otherwise be difficult to spot.
Faster Decision Making: By presenting data in an easy-to-understand visual format, data visualization enables us to make decisions quickly and easily.
Improved Communication: Data visualization makes it easier to communicate complex data to stakeholders. It helps to convey concepts and ideas in a way that is more engaging and easier to understand.
Increased Efficiency: Data visualization helps to streamline processes and reduce the time spent on analyzing data. This leads to increased efficiency and productivity.
Cost Savings: By reducing the time spent on data analysis, data visualization can help to save time and money.
As more organizations collect and analyze massive amounts of data every day, these data sets need to be processed rapidly in order to keep up with the influx of data. In this data driven era, this will help uncover insights which may be potentially helpful that would have otherwise been hidden.
Where does data visualization come in? Data visualization is that tool that will help you see just what this data is trying to convey. Data visualization will help present information gotten from data in a way that is quickly understood as well as communicate it in an efficient manner
However, because there are quite a number of ways to present data, it is important to choose the right visualization tool for the right data set. A great combination of the right data visualization tool to present the right data for a certain function can be a game changer for the growth of your organization.
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AegisDemoAdmin. (2022, April 6). The power of Data Visualization - Aegis - articles. AEGIS. Retrieved from https://aegisresearch.eu/the-power-of-data-visualization/
Is a solution and ROI-driven CTO, consultant, and system integrator with experience in deploying data integrations, Data Hubs, Master Data Management, Data Quality, and Data Warehousing solutions. He has a passion for solving complex data problems. His career experience showcases his drive to deliver software and timely solutions for business needs.
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