Do you know that we are generating 2.5 quintillion bytes of new data each day and that 90% of all the global data has been generated in the last 2 years only?

After reading this industry stat, it comes as no surprise that the overall data generated by global business enterprises doubles every 1.2 years. Apart from this fact, the data generated is also becoming more complex as they come from various data sources including social networking platforms like Facebook and Twitter, online cloud platforms, and connected Internet of Things (or IoT) devices.

With the growing complexity of business data, business enterprises are investing in data analytics tools that can analyze the large volumes of data and make it more meaningful for business insights and data-driven decision making. In this respect, effective data visualization is a useful model of representing business data in a graphical or pictorial form thus making it easy to analyze by a wider audience base.

Through this article, let’s delve into why data visualization is so critical for business enterprises along with the key principles that are necessary for effective data visualization.

All about Data Visualization

In simple terms, data visualization is the representation of complex business data in a graphical format. As a business enterprise, you can deploy data visualization software to interpret your business data and identify key data-driven patterns that can improve decision making.

How can the best practices of data visualization benefit any small or large business enterprise? Here are a few pointers:

  • Use of pictures, graphics, or images, that make it easier to understand new information and find useful trends.
  • Reduces your overall time and effort spent on data analysis.
  • Useful to a wider set of users including sales & marketing and finance heads.
  • Enables faster decision making in designing or revising key business strategies and taking business actions.
  • Improves your business ROI from data.

Why Data Visualization is important?

At a biological level, Data visualization concepts are very important because of the way human brains like to process any information. Rather than going through loads of numerical reports, a graphical representation of the data in the form of charts or graphs is much easier to grasp.

At an enterprise level, data visualization enable business enterprises to:

  • Identify their business strengths or areas of improvement.
  • Determine the factors that influence the online behavior of customers.
  • Arrive at the right strategy for product placement and pricing.
  • Predict future trends including sales volumes.

The Best of Data Visualization Tools

Data visualization tools are not only user-friendly but also provide users with a rich set of graphical features such as charts, graphs, infographics, maps, and videos to analyze and visualize data. While there are free data visualization tools available in the market, here’s our recommended list of the 3 best-paid tools for visualizing data:

  • Tableau

With over 57,000 active user accounts, the Tableau tool provides effective data visualization through functionalities such as big data visualization, smart data analytics, and business dashboards that are easy to design and deploy. With the use of technology that supports both artificial intelligence (AI) and machine learning (ML) applications, Tableau caters to a wide variety of industries including healthcare, education, and insurance.

  • Microsoft Power BI

Rated as an industry leader in the field of business intelligence (BI) and analytics by Gartner, Power BI is also rated highly for its data visualization capabilities. Easy to use, visualization can be directly created from the Power BI reports and includes a natural language feature that simplifies data querying. Additional features include inbuilt visualization elements that can be sourced from the AppSource community.

  • FusionCharts

Want to create rich and interactive JavaScript charts? Then FusionCharts is the right tool that supports over 100 types of interactive charts and over 1,400 data maps. Among its most unique feature, FusionCharts provides ready-to-use templates that make it quicker to implement data visualization.

While these tools can certainly simplify the visualization process, data analysts still need to apply key principles in the form of best practices of data visualization to derive maximum leverage from their data. In the following sections, we shall explore some of the best practices and design principles of data visualization along with some of the best data visualization examples.

The Best Examples of Effective Data Visualization

Want to make your “boring” business reports more interesting? Here are the best of effective data visualization examples:

  • A monthly business expense report that presents expenses across various categories (food, travel, operations) and the overall year-on-year employee expenses.
  • A financial report displaying the overall revenues, profits/losses, and cash flow of a business organization.

7 Key Principles of Effective Data Visualization

Listed below are the 7 key principles that you can utilize to derive actionable insights from data visualization:

  • Cater to your specific audience

No level of data visualization is useful unless it is designed to meet the information needs of its target audience that could include business customers or the company’s functional heads. As a guideline for data visualization, determine the data-related requirements of the audience and keep your data visuals simple to understand without adding any unwanted information.

An example of this principle is the User Behaviour visualization report that follows online user behavior trends particularly useful for the online retail or E-commerce industry sector.

  • Use visuals to grab audience attention

Being a visual tool, effective data visualization is all about including visual elements like charts, graphs, or interactive maps. Among a recommended design principle, use attractive color schemes or fonts to highlight visual elements that demand user attention. By making a visual element stand apart from the rest, visualization can convey the right information and message to the audience.

For example, this Web traffic acquisition report that uses effective visuals to highlight the more important metrics to the user.

  • Balance your design with the use of multiple elements.

What is a balanced design? Data visualization with an equal distribution of visual elements including the right shapes, colors, white space, and texture (or depth). As a data visualization design principle, evaluate any of the following balanced designs to see which fits your requirement the best:

  • An asymmetrical balance where both sides of the visual are the same.
  • An asymmetrical balance where both sides have different visuals but have the same (or similar) visual weight.
  • A radial balance where visual elements are placed around a central anchor object.
  • Include interactivity when necessary.7 Key Principles to Keep in Mind for

With most of the leading data visualization tools supporting interactivity, it’s now easier to integrate user interaction into visualized data. However, you should be prudent to include interactivity in your visuals only when they can benefit the user. The use of excessive interactive elements can confuse the user and divert their focus from the main data presentation.

  • Design your visualization for the mobile phone.

With the increase in the number of mobile phone users, the demand for data visualization on smartphones is growing. Visualized data in the form of stock price changes or industrial production-related data on a smartphone is now driving better actions and decisions.

As a data analyst, you need to design and optimize your data visualization for the mobile phone. This could include design practices such as:

  • Designing charts with the most critical information on the top left corner.
  • Use of appropriate color coding.
  • Zoom-in features online graphs to show data changes in detail.
  • Avoiding the use of graph titles and axis labels
  • Use data patterns smartly

What is a data pattern? It is used to display or compare similar sets of information. You can visualize a data pattern with the use of a consistent type of chart or the same color. Among the best-used principles of data visualization, data patterns are also useful to show any disruption in the information set that can attract the user’s attention.

  • Use of proportion

A proportion in the world of data visualization is used to display the comparative weights of different data sets, which are indicative of their values. For example, if you are showing the “market share” of a particular line of products, the product with the highest market share should be displayed with a bigger proportion (as compared to the rest). Pie charts are among the best visualization element to show proportion (as a data set with a “50%” proportion would be occupying a 50% pie size in the chart).

Here’s an interesting example of showing proportions in data visualization.


In an age of cluttered data and numerous data sources, data visualization provides business leaders and functional heads the ability to extract useful and relevant information that can impact their business strategy and planning.

With the use of personalized dashboards, Countants is enabling global customers to transform their critical data into valuable insights with its analytical and visualization capabilities. Be it the latest sales performance or conversion analysis report, Countants is the right partner for your journey into data analytics and business intelligence.

So, what are you waiting for? Get in touch with us now!