David has over 40 years of industry experience in software development and information technology and a bachelor of computer science
We live in a world where information rules. Or more precisely, where the ability to analyze and manipulate large amounts of information increases our understanding of the things around us. Examples include meteorologists gathering and organizing weather information to produce a forecast, recording banking transactions to determine account balances, and even looking at player and team statistics to try to predict game outcomes. The accuracy of our understanding is related, in part, to the amount of information we can digest. It will come as no surprise that the amount of data available is ever-increasing. In fact, the amount is getting too large for a person to handle. That is where an area like visual analytics comes in.
Visual Analytics is an area that applies analysis and reasoning to information sets using some sort of visual means. It combines the best of a person's capabilities (decision making, analysis, and reasoning) with the number crunching capabilities of a computer. And, it does this through a visual interface.
Let's look at an example. We have all seen the weather animations available on our favorite weather website. In these animations, the computer presents us with a graphical display of the expected temperature and precipitation in our area, cloud cover, wind speed, and how the computer predicts they will change over time. We watch these animations and make choices, maybe about whether we need a coat or an umbrella for that day.
Visual analytics can be used for any number of things. And as you might imagine, there are a number of factors that can influence their use. They include:
There are a number of visual analytics tools available. Some examples include:
To recap, visual analytics applies analysis and reasoning to information sets using a visual interface. The use of visual analytics is influenced by a number of things including the amount of information, the complexity of the information, the point-of-view of the viewer, and the technical nature of the viewer. There are a number of visual analytics tools available including Dundas, Sisense, IntelliFront, and Domo.
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