Data Visualization Best Practices for Business Users
Data Data Visualization Digital Transformation

Data Visualization Best Practices for Business Users

In the words of British journalist and writer, David McCandless, “Visualizing information can give us a very quick solution to problems.” 

With the increased use of electronic devices and globalization, the volume of data is expected to grow exponentially. According to IBM, 2.5 quintillion bytes of data are created every day, and going by IDC’s prediction, there will be 163 zettabytes (163 trillion gigabytes) of data by 2025. 

With so much information being collected through data analytics tools, you must have a way to paint a picture of that data to interpret it. For any human brain, it is challenging to comprehend such large amounts of data without drawing analogies or useful abstractions. This is where data visualization is useful. 

Data Visualization for Business Users 

Data visualization is the visual representation of numerical data in some schematic form like line graphs, pie charts, bar charts, and maps – that can be used to extract useful business insights. 

Data visualization plays a crucial role in making accurate business decisions – in varied areas including economics, finance, or technology. How can you use data visualization efficiently as a business user? 

Here are ten of the best data visualization practices that are crucial for the best results:

1) Know your business goals

In today’s business environment, data has a different meaning or goal for different functions. For example, data analysts have different data-specific goals as compared to a company’s CEO or HR manager.

Before deploying data visualization, every business function must answer questions like:

  • What is my business goal?
  • What is the data-driven information that I am looking for?
  • What is the expected outcome from visualization methods?

Depending on these factors, data visualization can answer business-related queries and solve real business problems. For instance, marketing teams can use visualized data to track their campaign performance and monitor customer metrics. 

2) Identify the target audience for your visualized data

Apart from knowing your business goals, determine the target audience for whom you are visualizing the data. Further, what do you want your audience (or intended users) to take from these visualized insights?

Data visualization is not a one-size-fits-all tool. Based on the intended audience, ensure that visualized data empowers your users and not just distributes relevant data. For example, knowing “the number of paid distribution channels that have been used over the previous 12 months” is useful for your sales head and marketing manager to plan the next set of campaigns.  

Designing your visualization techniques and methods around your target audience can be both effective and empowering. Depending on your business domain, your potential target audience can range from data scientists, digital marketers, social media managers, web designers, and many more. 

3) Make sure you use the correct data

Research scientists Andrew McAfee and Professor Erik Brynjolfsson of MIT point out that around 2.5 exabytes of data are created every day, which is being doubled every 40 months. 

With so many data sources to choose from, make sure you retrieve your data from the right source. Here are a few tips to ensure this:

  • Use data that are qualitative (with sufficient data points), ordinal (with a logical sequence), and categorical (or grouped).
  • Avoid any data points that do not support your overall story. 

4) Choose the right chart type for data visualization

Which type of visual chart works best for which data? While line charts work best for showing data variations or patterns over time, bar charts work best when comparing data across categories. 

An example of a bar chart is the monthly sales of a company across its product categories. On the other hand, scatter plots work best for data across 2 factors (example, number of sold product units for each month of the year).

Apart from choosing the right chart types, make sure to use proper chart labels so that the data is easily understood by any stakeholder.

5) Use an organized and coherent design

How can you compile and show Big Data through visualization? An organized and coherent design is essential for your audience to process the information efficiently.

Here are some tips to make a coherent visualization design:

  • Show data in sorted order (either increasing or decreasing). For example, the percentage of female technology workers between 1980 to 2020.
  • Use of colour highlights across related data points that emphasize which of them are important (or not). For example, a visual depiction of a World happiness report using a world map with colours.

6) Provide context to build trust

Contextual data allow experts to see data patterns and make future predictions or recommendations. Building context into visualized data determines how a particular data set compares to data from the previous day, month, or year. 

Data visualization can also help interpret the numbers against set metrics or thresholds. For example, “the number of subscribed monthly users” crossing the 10,000 mark. How do you build context into data? By using visual elements like colours, arrows, or percentages.

7) Simplify your visualization dashboard

Dashboards offer a simplistic way of showing visualized data. Be it high-level strategic or operational dashboards, present your visualized content with a simple design that is easy to comprehend.

Here are some useful tips for designing a great dashboard:

  • Add the right metrics that are relevant to the business users (for example, customer-centric metrics for marketing teams).
  • Contextualize your numbers (example, increase (or decrease) in today’s customer conversions as compared to yesterday).
  • Maintain a consistent look to your dashboard (for example, by using the same visualization charts and layouts).

8) Design to keep users engaged

As a business practice, you can encourage your users to engage with visualized data, to drive them to uncover data insights on their own. 

Here are some ways to facilitate user engagement:

  • Scheduling email reports regularly – for example, to generate a report for “product-wise revenues” using data filters.
  • Automatic metric-driven notifications, which are generated whenever a specific metric goes below or above a configured value (example, number of active session users).

9) Ensure your data is readable on multiple devices

Should your visualized data be compatible with all personal devices? Yes, considering the growth of personal devices like laptops, tablets, and mobile phones. 

Here are some tips to make your data visualizations readable across devices:

  • Use of CSS format that works for all devices, without changing the HTML code every time.
  • Image optimization for fast loading.
  • Use of design contrast to make vital visual elements stand out from the rest.

10) Keep improving 

Finally, data visualization is all about simplifying the data and “telling a story.” Data visualizations are open to different user interpretations. 

Here are a few tips:

  • Share your dashboards and visualizations with your business peers or office colleagues for their interpretations.
  • Be open to accepting and incorporating their feedback and comments to improve your data visualizations. 
  • Avoid the use of old data visualization practices and tools. 

With the growing volume and complexity of Big Data, data visualization is an important tool for business users. Efficient data visualization practice can process and interpret complex data and make it simple to understand for your target audience. 

This list of 10 best practices ensures that your data visualizations always remain engaging, convincing, and compelling. 

Need more data insights? You can seek help from Heptagon. We make sure to deliver data in a format that helps you make better business decisions. Contact us today! 

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