Data Visualization is Key

Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from.

Why is this helpful?

Data Visualization makes it easier to identify patterns, trends and outliers in large data sets.

Did you know?

Data Visualization is an important step of the data science process, which states that after data has been collected, processed and modeled, it must be visualized for conclusions to be made. It is also an element of the broader data presentation architecture discipline, which aims to identify, locate, manipulate, format and deliver data in the most efficient way possible.

It is not only helpful for scientists, but every career. Teachers use data visualization to display student test results; computer scientists use it to explore advancements in artificial intelligence; and executives use it to look at and share information with stakeholders in a concise and easy to understand manner. With businesses accumulating massive collections of data during the early years of the big data trend, they needed a way to quickly and easily get an overview of their data. Visualization tools were a natural fit, and you should utilize it too!

Why is data visualization important?

Data visualization provides a quick and effective way to communicate information in a universal manner using visual information. This practice can also help businesses identify which factors affect customer behavior; pinpoint areas that need to be improved or need more attention; make data more memorable for stakeholders; understand when and where to place specific products; and predict sales volumes.

In short, data visualization is important because it is:

• Quick and effective – it facilitates the ability to absorb information quickly, improve insights and make faster decisions
• Easily understandable – an increased understanding of the next steps that must be taken to improve the organization
• Engaging – helps improve your ability to maintain the audience’s interest with information they can understand
• Participative – easier distribution of information through these visualization methods increases the opportunity to easily share insights with everyone involved
• User-friendly – eliminates the need for data scientists since data is more accessible and understandable
• Efficient – with an increased ability to act on findings quickly it therefore facilitates success with greater speed and less mistakes

The psychology of data visualization

Data helps us to make sense of our world. We draw meaning, find patterns, make associations, create maps and models which help us get insights, understand trends, and make informed decisions. We seek and remember the stories that data tells.

A well-made and designed data visualization portrays a large amount of complex information using relatively little space and by taking advantage of our visual system. This is why data visualization is one of the most convincing methods to share the various kinds of data that is extracted from all the systems available to us today.

The relevance of data visualization is even more pronounced in light of ever-decreasing attention spans.

Let us understand exactly how the psychology of data visualization works!

The effectiveness of data visualization is in its ability to represent information in a manner that our eyes can recognize, and our brains can understand quickly. The goal is to transform abstract information into visual representations that can be easily, efficiently, accurately, and meaningfully understood.

These visualizations are understood and remembered because:

• They clearly indicate how values relate to one another. Relatable content always helps recall.
• They represent the values accurately by using graphs or charts to indicate values.
• They make it easy to compare values. Evident comparison makes things easier to remember.
• They make it easy to rank and order the values. This helps to organize various values in our minds to understand them better.

Data visualization can make it obvious how people should use this information, what they should use it to accomplish, and encourage them to follow through.

As the saying goes, “a picture is worth a thousand words”; this is true when a story is told graphically, with a strong design, instead of verbally. For example, you could stare at a table of numbers all day and never see what would otherwise be very obvious to notice while looking at the same numbers graphically well represented.

While words and numbers can express values precisely, pictures or graphic representations have the power of allowing us to identify and highlight patterns, trends, or exceptions among these values. This is important if we want to compare entire sets and large amounts of values rather than just two at a time. Alpha numerical data, such as text in a table, is interpreted by our brains through the use of verbal processing. This does not always communicate as effectively to our brains as data that is communicated visually, which we are able to easily understand and interpret.

This is the power of data visualization.

Though data visualization usually features relationships between quantitative values, it also has the capability of displaying relationships that are not quantitative in nature. For example, the connections between people on a social networking site can be displayed using a node and link visualization. However, visualizations that feature relationships between entities, such as the people in this example, can be enriched with the addition of quantitative information as well. For example, the number of times that any two people have interacted could be represented by the thickness of the line that connects them.

How the brain processes data visualizations – let’s get into the science of it

Data visualizations are so effective because they shift the balance between perception and cognition to take better advantage of the brain’s abilities. Seeing (visual perception), which is handled by the visual cortex located in the rear of the brain, is extremely fast and efficient. Thinking (cognition), on the other hand, which is handled predominantly by the cerebral cortex in the front of the brain, is much slower and less efficient. This suggests that traditional making sense of data and its presentation methods require conscious thinking for almost all of the work. However, data visualization shifts the balance towards significant use of visual perception, taking advantage of our eyes and speed of seeing.

Why data visualizations help us to understand faster

Our brain has the capability of detecting shape, color and motion separately which allows our audience to understand, make associations and identify dimensions in data visualizations almost instantaneously. Utilizing data visualizations that incorporate pre-attentive features (processed incredibly quickly, within around 10 milliseconds) make them much more effective thanks to pre-attentive processing, which is the subconscious accumulation of information from the environment, where all the available information is pre-attentively processed. Then, the brain filters and processes what is important. Information that stands out the most or is of most relevance to what a person is thinking about is selected for further and more complete analysis by attentive processing.

This therefore goes to show that a well laid out dashboard with helpful visualizations of data can really enhance the speed, and accuracy with which we can interpret data and glean useful information. Charts and graphs with various shapes and colors can assist in speedy assimilation information and worthwhile comparisons.

Data visualization tools and vendors

Data visualization tools can be used in a variety of ways. Companies can set up visualization tools to generate automatic dashboards that track company performance across key performance indicators (KPIs) and visually interpret the results.

A great software can offer features such as:

• Effective Visualizations – use of various diagrams (for example: bars, lines, pies, areas, maps) or context-specific highlighting (for example: arrows, colors, markers).
• Filters – distributes dashboards and reports according to individual requirements such as customers, periods, products, regions or sales assignments.
• Interactivity – Possibility for simple drill downs to detailed data or expansions of structure information.
  Flexibility – allows further editing of dashboards and reports in Excel, PDF, as graphics or as printouts.
• Various Levels of Detail – Creation of dashboards and reports from top management level, down to operational detail level, according to individual requirements.

As data visualization evolves and extends the functionality of these tools, they are increasingly being used as front ends for more sophisticated big data environments. In this setting, data visualization software helps data engineers and scientists keep track of data sources and do basic exploratory analysis of data sets prior to or after more detailed advanced analyses. Also, businesspeople use it to transform their sales channels and revenue streams.

Now that you understand what data visualization is, as well as the psychology behind it, shouldn’t you too be utilizing such visualizations for information analysis? A proper dashboard will help to display information in such a helpful way.

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