What is Visual Analytics?

Visual analytics is a form of reasoning that uses interactive, visual interfaces. Visual analytics uses data analytics and interactive visual representations of the data and dashboarding to enable users to interpret large volumes of data. Data visualizations alone are very useful as they help you answer the “what” questions - like “what are the problems”, or “what are the trends.” However, when searching for insights in the data, you need to be able to ask why. That is the power of visual analytics as it allows you to dig deeper into the data. You can quickly build different views and different types of visualizations in the data to get to your answer, beyond the constraints of a templated dashboard, to better understand the trends or answer the questions that you have. Data visualizations answer the “what” questions, but visual analytics help you get to the “why.”

Visual analytics combine visualization, human factors, and data analysis to gain knowledge from data. When presented visually, analytics are easier and faster for users to interpret. Visual analytics make complex issues much easier to understand and are especially useful for those users that are not data scientists or know complex statistical algorithms. However, both data scientists and business users can find visual analytics useful. The interactive and visual elements are often helpful in communicating what one sees in the data to others and in making better-informed business decisions.

Even though many data analytics operations have been automated in recent years, human intervention and interpretation is still needed to get you to the next level in your data exploration. There are interpretations and analyses that a computer just can’t do. This is why visual analytics is so important.

Exploring your data with visual analytics

The beauty of visual analytics is that it gives you a real time view of your data and allows you to manipulate your data easily and quickly without having to know how to build charts and other visualizations. You can also quickly and easily change the data that you are looking at and the type of visualization to help guide your exploration into the data. And, your manipulations do not change the data. So, you can also easily go back in steps if you need to retrace what you did or take a different route in your journey. As you create different views of your data, the meaning in your data unfolds, leading you to more and sometimes unexpected outcomes. With data analytics, you don’t necessarily have to know where you are going to come upon insights.

Visual Analytics Example

What is the benefit of visual analytics?

Visual analytics can help with more easily interpreting data and therefore making analytics more user-friendly to non-experts. This can allow for the democratization of data analytics across an organization, involving business users in the analysis of data that inform its decisions. Since the data is displayed in an interactive, graphical way, business users can uncover insights in the data without waiting for IT to deliver answers and therefore make smarter decisions faster. Visual analytics also enable insights and findings to be quickly shared among important stakeholders where you can also collaborate easily to find the right answers. Visual analytics helps the entire organization get to insights faster.

Visual analytics enable you to not be constrained by a chart type or visualization so you can think and search freely. When you are constrained by that, your analysis can become limited. With visual analytics, you can visualize data from different sources (different databases, different social media, etc) in one view.

With visual analytics, the steps of querying, exploring and visualizing data come together in a single process. Visual analytics leads to fast exploration, iteration, and prototyping data to support the way you think so you can arrive at conclusions or more questions quickly and easily. No matter how complicated your question and answer process, visual analytics will support your analysis which leads to better business decisions.

Visual analytics vs data visualization

Visual analytics and data visualization are often used interchangeably. However, the two have different capabilities and purposes. Both give you a specific set of data to answer specific questions. Both give you visual ways to represent data, making it easier to communicate findings and telling stories with your data. Both give you data points, highlight problems and key indicators. However, that’s as far as the similarities go.

Visual analytics help you answer the “why” questions in your data. Visual analytics uses advanced analytics to help you visually explore your data, without having to know where you are going in your exploration journey. Visual analytics often leads to unexpected findings and insights that bring up issues or indicators that you were not even aware of.

It’s best to think of it like this: Data visualizations help you answer the “what” and data analytics help you dive deeper into your data and answer the “why.”