How to get more from your data with better visualization

Data visualization

A picture is worth a thousand words: Create and narrate compelling data stories.

Impactful data visualizations allow business leaders to analyze information, draw conclusions, and make data-driven decisions in a timely manner. Recent studies have shown that 94% of enterprises recognize data and analytics visualizations as a foundation for digital transformation and a key enabler for business growth. 

Data analytics recognizes patterns and derives meaning from complex data sets. It deals with structuring and analyzing data. Data visualization, however, represents this information as charts, graphs, or other forms of visual representations to develop trends and conclusions.

A 360-degree view of data

Data visualization spans what happened, why it happened, what is likely to happen in future, and what action must be taken.

With its ability to visualize large data sets and draw insights, data visualization can address areas that need attention as well as discover new patterns in data. For visualization to be impactful, it is important to make it effective and engaging.

Effective visualizations are clear, interactive, and user-friendly. They communicate information briefly that enables users to extract actionable insights, identify trends and patterns, and find improvement opportunities through an easy data analysis process. Considering these needs, the basis for an efficient visualization design should be to prioritize the most relevant data, designed for focused user groups, and guided by core business goals.

Through active participation in data discovery such as clicking, scrolling, and hovering, users can engage with data keenly and uncover insights that help in decision making. 

Design principles

Let’s look at six key design principles for effective data visualization

• Select the right presentation: Select the right graph or chart type depending on the use case for a specific purpose and a specific audience.

• Include clear labels: Labels define and qualify the data, and they should be clear and concise. Providing titles, headings, sub-headings, units, and data points in graphs makes the information self-explanatory. 

• Use appropriate colors: Colors and gradients help highlight information and key messages—they differentiate and identify anomalies, outliers, and trends. In addition, make sure you select from the standard colors or color schemes defined by your organization. 

• Look for ways to incorporate sorting: Sorting the data improves readability and helps the audience draw conclusions quickly, especially in tabular representations. Whenever possible, give users the flexibility to sort the data through different data attributes.

• Call out important KPIs and sequence the layouts effectively: Identify the important KPIs and place them at the top to give a quick overview of the data. Place common elements such as filters at the top to allow for faster navigation. 

• Optimize for multiple devices: Users often access data on various devices such as mobile devices, laptops, and computers. Make sure the visualization layout is optimized appropriately for different devices that are being used by the target audience.

Engaging the audience

Five techniques to make data visualization engaging 

An engaging visualization converts passive users into active participants. This increases their participation in the data discovery process and leads to improved interaction and engagement. 

The following techniques can make data visualization engaging:

• Always keep your target audience in mind: Understand the requirements of the audience that will be consuming the data, including their level of expertise in the subject and the depth of information they might find helpful. For example, CXOs may be more interested in summarized information rather than minute details. The better you understand your audience, the higher the odds of you conveying a clear and to-the-point message that has a lasting impact.

• Tell a story: Storytelling is presenting data in a visual manner that shows the entire narrative gleaned from the data analysis. It helps to efficiently understand business strategies and goals. Data storytelling simplifies complicated information so that the audience can engage with the content and make critical decisions quickly and confidently. 

• Incorporate interactive elements: Leverage interactivity features of your data visualization tool to engage the users. Interactivity encourages exploration and helps to find answers to questions the viewer might have. Visualizations can be made interactive by including elements such as filters, parameters, and hyperlinks. A drill-down feature can allow the user to explore more detailed information related to a particular dimension, data point, or KPI without crowding the overall design.

• Keep visualization simple: Show only an adequate amount of information. Avoid using unnecessary gridlines, distracting visual patterns, redundant axes, shadows, too many tick marks, or anything that causes clutter. If required, additional information can be included in tool tips. 

• Optimize for performance: An effective and engaging visualization should not take long to load while opening, interacting with elements, or while refreshing data. Optimize to strike the right balance between visualization and performance. Data visualization plays a vital role in identifying and presenting key information with ease and simplicity. Following effective and balanced dashboard design principles will give business leaders valuable and actional insights and help them in accelerated decision making for business growth.