Data Visualization: What is it?

In our increasingly data-driven world, it’s more important than ever to have accessible ways to view and understand data. After all, the demand for data skills in employees is steadily increasing each year. Employees and business owners at every level need to have an understanding of data and its impact. That’s where data visualization comes in handy. With the goal of making data more accessible and understandable, data visualization in the form of dashboards is the go-to tool for many businesses to analyze and share information. 

What is Data Visualization?

Data visualization is the presentation of information in a more insightful format – like a graph, chart, scatter plot, or diagram. This process reveals trends from thousands or millions of data points. And, seeing information presented visually makes it easier for the human brain to derive insights.

While you can always put data into an Excel spreadsheet to compile information, data visualization can showcase the same data in ways that take insights much further. Business intelligence tools combine and layer large data sets. Using real-time interactive updates, these tools make it possible to create data visualizations that improve humans’ ability to interpret data. Simply, they give your company a better way to understand the information you’re collecting.

With data visualization, you can find unexpected trends and get a crystal clear view of your financials, sales figures, and customer information.

Why is it important?

The importance of data visualization is simple: it helps people see, interact with, and better understand data. Whether simple or complex, the proper visualization can bring everyone on the same page, regardless of their level of expertise.

It’s hard to think of a professional industry that doesn’t benefit from making data more understandable. Every STEM field benefits from understanding data, as do fields in government, finance, marketing, history, consumer goods, service industries, education, sports, and so on.

While we’ll always wax poetically about data visualization there are practical, real-life applications that are undeniable. And, since visualization is so prolific, it’s also one of the most useful professional skills to develop. The better you can convey your points visually, whether in a dashboard or a slide deck, the better you can leverage that information. The concept of the citizen data scientist is on the rise. Skill sets are changing to accommodate a data-driven world. It is increasingly valuable for professionals to use data to make decisions and use visuals to tell stories of when data informs the who, what, when, where, and how.

While traditional education typically draws a distinct line between creative storytelling and technical analysis, the modern professional world also values those who can cross between the two: data visualization sits right in the middle of analysis and visual storytelling.

How is data visualization used?

Data visualization can be used in a variety of ways. Many times, data visualization storytelling is only limited by the availability of good data and the resources (whether people or software) to convert that data into pictures. Some ways data visualization is used include:

• To identify trends, such as whether sales are going down or certain processes are not as productive as they were
• To understand complex information quickly, such as when people view dashboards to conduct an overall process health check
• To identify patterns, such as whether the first Wednesday of the month always has a spiked call volume
• To identify relationships, such as whether the night production processes flounder whenever a certain person is in charge
• To examine a network, such as which audiences marketers should target with their message
• To analyze risks and address issues before they become problems
• To communicate a story that gets the message across to your organization quickly
• To identify the frequency, such as how often a product is purchased in a specific area
• Understanding all of the above types of data helps businesses discover root causes for issues, identify winning scenarios, and make decisions that lead to more positive outcomes.

Some benefits

Bring insights faster

Empower everyone to transform data into insights quickly and easily. Data visualization allows easy discovery of trends and faster identification of outliers. The information helps build an understanding of how the business is performing and what opportunities and risks are developing.

Make smarter, faster decisions

Organizations can make fast data-driven decisions with visualizations that display real-time data in invaluable, informative ways. By comprehending the information and collaborating with others to spark insights and spot patterns in data faster, the days of relying on gut instinct to make quick decisions are long gone.

Empower everyone with advanced analytics

Now more of your organization can benefit from easy-to-use interactive dashboards with built-in geospatial, one-click predictive, and stream analytics to develop deeper insights, discover hidden patterns, and act on high-value business opportunities.

Improve the value of your product or service

Data holds an incredible amount of value, yet most users don’t have the time or patience to learn a specialized business intelligence tool. Make data convenient and intuitive for users by embedding analytics in their apps and business processes.

Spend less time on custom analytics requests

Save your technical teams from writing custom code for every report or visualization and from repetitive, time-intensive tasks. Instead, allow them to focus on building your core product or service by enabling end-users to visualize and get answers from data all on their own.

What are the two main types of data visualization? Exploration vs. explanation

We’ll look at specific types of data visualization later on, but for now, it’s important to distinguish between exploratory and explanatory data visualization.

In a nutshell, exploratory data visualization helps you figure out what’s in your data, while explanatory visualization helps you to communicate what you’ve found. Exploration occurs while you’re still analyzing the data, while explanation comes toward the end of the process when you’re ready to share your findings.

Exploration

When faced with a new dataset, one of the first things you’ll do is carry out exploratory data analysis. This is where you investigate the dataset and identify some of its main features, laying the foundation for a more thorough analysis. At this stage, visualizations can make it easier to get a sense of what’s in your dataset and spot any noteworthy trends or anomalies. Ultimately, you’re getting an initial lay of the land and finding clues as to what the data might be trying to tell you.

Explanation

Once you’ve conducted your analysis and have figured out what the data is telling you, you’ll want to share these insights with others – key business stakeholders who can take action based on the data, for example, or public audiences who have an interest in your topic area. Explanatory data visualizations help you tell this story, and it’s up to you to determine which visualizations will help you to do so most effectively. We’ll introduce some of the most common types of data visualization (and when to use them) in section four.

Get your data ready for visualization

Data visualization helps you solve problems. Whether it’s client contact information or financial performance stats, your data holds the secrets to improving, optimizing, and growing your business. With AI-augmented data cataloging and data quality solutions, you can find and rectify problems in your data you didn’t even know you had to improve your data visualizations.

Working with the best, most accurate data gives you an edge. With the insights data visualizations provide, you remove the guesswork and take a necessary step toward making better more informed decisions.