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Data Visualization

Top 10 Best Practices for effective Data Visualisation

Dr. Jagreet Kaur Gill | 23 November 2023

Data Visualization Best Practices

Introduction to Data Visualization

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 visually makes grasping, analyzing, and counting as best practices easier. It also helps in decision-making faster and finding new hidden patterns to understand complex concepts better.

When information is represented in graphic form, a human can realize more frequently and quickly even complicated things. Yet it does not require any technical skills and is easy to learn with the help of various tools like Power BI and Tableau

Three-dimensional visualization can be used for morphological correlation between different classes of volumetric data, such as those acquired using different types of.

10 Best Practices for Data Visualization

We all want our Business Intelligence (BI) and analytics solutions to transform data into insights. However, the data is handy only if understood and shared better. In this section, we will be listing the best practices below:

  1. Entitle a specific audience and mark their needs
  2. Choose the right visual (The Key)
  3. Apply Text Carefully and Intentionally
  4. Use the predictable pattern for layouts
  5. Select the right tool
  6. Use attractive colors for telling data stories
  7. Use beautiful and straightforward Dashboards
  8. Try to make visualization inclusive
  9. 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 customer data. There might be chances that one is not fit for all. We must put more effort into 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 facing? 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 risky? Is this profitable or not? Whether I buy this property or not. Sometimes, a decision must be answered multiple times a day or even a week or month at a meeting. So, the visualization should be created in such a way it will give a binary response to you.

Get more information related to data visualization.

Choose the Right visual (The Key)

Once you know your audience and the data, it is time to select the correct type of visual that best expresses the information included in the data:

Line Chart

When we want to represent continuous data with minor 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. For example, time spent on a smartphone, compare which field had the highest profit, or compare the paid and unpaid apps downloaded by types of gadgets.

Pie 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 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 multiple items within a particular range. In this example, we compare the profit of a particular product in a specific country.

Area Chart

Using area charts to show how values develop with time is good practice. It is 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

Put all the vital points at the top or upper left corner because the human eye is drawn to 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 be difficult to understand. When applying multiple filters, group them and add a border around them to make them more transparent and attractive.

Use the Predictable Pattern for Layouts

Human eyes quickly catch indicators that help in understanding important information. You usually grab designs; 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 must represent data that makes sense to viewers, whether sequential or numeric. If you are using no graphs, ensure the chart is appropriately visible, and connections between data should be clear. Please don’t confuse your viewers, as it is not counted in its best practices, and users can quickly go from one point to another.

Select the  Right Data Visualization Tool

The data visualization tools differ from developers to Data Engineers to Data Analysts to BI Engineers. Some of the Tools that are Famous among the community are -
A. Echart 
B. Highchart 
C. Tableau
D. Fine BI
E. Power BI

Deep knowledge of Power BI with data visualization.
F. Ali DataV
G. FineReport
H. Digital Hail

Know more in detail about data visualization tools.

Data Visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

Use attractive colours for telling Data Stories

Colours 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 colour 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 colours. For example, in a graph, use different shades of particular colours 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, the dashboard usually contains many graphs, so try to add three or four charts or graphs for better understanding. Try to use different colours 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 the dashboard is clear and attractive, it helps to grab the viewer’s attention.

Explore more about the use of dashboards in data visualization.

Design in such a way that the user should be engaged

Designing the dashboard the user should be engaged in is one of the most critical Data Visualization Strategies. For compiling data into data, visualization consistency is essential. A great visualization helps the observer to conclude faster and more efficiently. They perfectly show data. Display on the data hierarchy supports the observer in making a decision quickly. The designer can sort the data from 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, font, and various other elements in charts help viewers interpret data more efficiently.

Try to make visualization inclusive

How we represent data using different colors helps people understand the dashboard better. According to a recent review, it is a critical factor in observer decisions. People responded to other color combinations faster than similar colors used in charts. Using identical colors with fewer contrasts creates difficulty for average viewers, sometimes even more difficult for those with vision problems. Its best practices include using the right contrast combination. To convey different types of information, try to use different patterns. For label elements, try to use text and icons. 

Examine Business Insights and Analytics

In this competitive world, it is tough to find data interaction. This is one of the most essential best practices emphasizing finding 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 providing a quality product to customers. It also helps in finding a problem before it arises. You can stay at the top of trends, which enables you to increase your profit

Best Practices - Turning Data into Insights 

Data visualization helps handle a large amount of data shown in meaningful charts and graphs. We need the best visual tools, like Power BI, tableau, and many more. Always try to choose the tool according to your requirements. The device should support maximum interactivity, be attractive, combine data sources, and share 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.