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Introduction to Data Visualization
“The greatest cost of a picture is when it arms us to notice what we have never waited to see.”
Data Visualization is a method of translating raw data into visual forms like charts, graphs, and maps. It has quickly become famous for publishing information on the web. It helps in a wide variety of industries, from business intelligence to journalism, for better knowledge and conveys the vision within data. Displaying data in visual form makes it easier to grasp and analyze and count as best practices for it. It also helps in decision-making faster and finding patterns, including new and hidden, to better understand difficult concepts.
When information represents in graphic form, a human can realize more frequently and quickly even complicated things also. Yet it does not require any technical skills and is easy to learn with the help of various tools like Power BI , and Tableau. Before we get started with its best practices, let's get to know some history.
Three-dimensional visualizations developed to provide both qualitative and quantitative information about an object. Click to explore about, 3D and Multidimensional Data Visualization
An Illustrated History
The theory of it is not new. Even it has been around for centuries. The first and most obvious examples are maps. Then the pie chart came into play in the 19th century. After a few decades, Charles Joseph and Minard used graphs to draw maps of Napoleon Bonaparte’s Russian campaign of 1812 with different metrics like several armies, temperature, and distance. Some more highlights in its history of it include Oresme, one of the best thinkers of the middle ages, who invented the bar chart in the 14th century, and Playfair was awarded the first use of the area chart.10 Best Practices for Data Visualization
All of us want our Business Intelligence (BI) and analytics solutions to transform data into insights. However, the data is handy only if understood and shared it in a better way. In this section, we will be listing the best practices below:
- Entitle a specific audience and mark their needs
- Choose the right visual (The Key)
- Apply Text Carefully and Intentionally
- Use the predictable pattern for layouts
- Select the right tool
- Use attractive colors for telling data stories
- Use attractive and straightforward Dashboards
- Try to make visualization inclusive
- Examine Business Insights
Entitle a specific audience and mark their needs
Constructing visualization and putting all of them together into a dashboard is not a way of providing data to the customers. There might be chances that one is not fit for all. We have to put more effort than just sharing performance with others, monitoring behavior, and measuring effectiveness. We have to answer these questions also:-
For whom are we designing visualization?
While designing a dashboard, we must know our priority persona. What challenges are we doing to face? How do we solve these challenges? Design the dashboard in such a way that meets all the requirements of users.
What decision do I need the user to make?
It must answer what decision I should take. Is this decision is risky? Is this profitable or not?. Whether I buy this property or not. Sometimes a decision needs to be answered multiple times a day or even a week or month at a meeting. So visualization should be created in such a way it will give a binary response to you.
Choose the right visual (The Key)
Once you know your audience and the data, it is time to select the right type of visual that best expresses the information included in the data:Line Chart
When we want to represent continuous data with small changes, we use a line chart. It works well for a high number of values with different time intervals.Bar Chart
When we want to compare data, there can be a horizontal or vertical bar chart. Example Like time spent on a smartphone, compare which field had the highest profit or compare no of paid and unpaid apps downloaded by types of gadgetsPie Chart
Mainly the pie chart is used for representing the proportion or percentage of data. It is useful when we have less than seven categories. It also helps in determining at what percentage that particular category holds.Column Chart
It is used when we want to compare various categories with subcategories. It is also used to compare various items within a particular range. Like in this example, we compare the profit of a particular product in a specific country.Area Chart
It is good practice to use area charts when we want to show how values develop with time. It mainly used when we want to know the exact share of a particular category. It helps to represent a significant difference between values.Apply Text Carefully and Intentionally
At the top or upper left corner put all the vital point because the human eye is drawn that place first. Try to add three or four views in a single dashboard as it is one of the best practices for it. Because if we add too many graphs, it will difficult to understand. When applying multiple filters, group them, and add a border around it to make it more transparent and attractive.Use the predictable pattern for layouts
Human eyes quickly caught indicators that help in understanding important information. You usually grab patterns, and if they are random or don’t make sense, sometimes it is tough to understand what visualization wants to communicate. To know about human thinking, we have to represent data that make sense to viewers, either it is sequential or numeric. If you are using no graphs, make sure the chart should be properly visible, and connections between data should be clear. Don’t let your viewers get confused as it is not counted in its best practices and users can quickly they can go from to point to another.Select the right data visualization tool
The tools for visualization of data defer from developers to Data Engineers to Data Analysts to BI Engineers. Some of the Tools that are Famous among the community are -- Echart
- Highchart
- Tableau
- Fine BI
- Power BI
- Ali DataV
- FineReport
- Digital Hail
Explore Best Data Visualization Tools and Platform in 2023
Use attractive colors for telling data stories
Colors play an important role in depicting graphs without using words. It helps to communicate a lot about your visuals. Try to keep it simple as it is one of the best practices for it. Using color for highlighting essential points helps to understand the dashboard more frequently and quickly. Proper Color clubbing matters a lot. The viewer can understand faster and promptly try to use natural colors. For example, in a graph, use different shades of particular colors to show a profit for a specific month and the brightest for a month have the highest benefit.Use attractive and straightforward Dashboards
As we know, most of the time dashboard contains a number of the graph so try to add three or four charts or graphs for better understanding. Try to use different colors for different figures for better knowledge of viewers because the dashboard is the main thing that will help the viewers to get the result and make decisions accordingly. If we made a dashboard clear and attractive helps to grab the viewer’s intention.Design in such a way user should be engaged
Designing the dashboard that the user should be engaged in is one of the most important Data Visualization Strategies. For compiling data into data, visualization consistency plays essential. A great visualization helps the observer to conclude faster and efficiently. They perfectly show data. Display on the hierarchy of data supports the observer for making a decision quickly. The designer can sort the data into highest to lowest to highlight the most crucial point to the viewer in the most prominent way. Even in which order we display data, the colors we used, the font we used, various other elements in charts help viewers to interpret data more efficiently.Try to make visualization inclusive
The way we represent data using different colors helps people to better understand the dashboard. From the recent review, it is a critical factor in observer decision. People responded to different color combinations faster than similar colors used in charts. If we use identical colors with fewer contrasts, create difficulty to average viewers, sometimes even more difficult for them who have a vision problem. Its best practices include using the right contrast combination. To convey different types of information, try to use different patterns. For labels, elements try to use text and icons.
Examine Business Insights
In this competitive world, it is tough finding data interaction. This is one of the most important best practices for it, that emphasis you to find data correlation in business insights. Examining these insights is very important for every business so that they can set the right track for achieving their goals. It also helps in getting knowledge of the latest trends and provide a quality product to customers. It also helps in finding a problem before they arise. You can stay at the top of trends which helps you in increasing profit
Conclusion
Data visualization helps in handling a large amount of data that will be shown in the form of meaningful charts and graphs. To do so, we need the best visual tools that are available in the market, like power BI, tableau, and many more. Always try to choose the tool according to your requirement. The tool should support maximum interactivity, be attractive, combine data sources, sharing dashboards with other viewers. Always try to create a neat and clean dashboard that helps viewers with a better understanding of data and also helps in decision-making.
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