Visual Analytics (VA) is an established, multidisciplinary field: “the science of analytical reasoning facilitated by interactive visual interfaces” (Thomas & Cook, 2005). Human analysts use VA to take masses of data, in forms that are often not clear to stakeholders, and visualize it interactively in ways that transform the data into meaningful visualizations, revealing hidden patterns and problem solutions to that audience. VA takes advantage of the powerful visual intelligence and cognitive capabilities of human analysts: Humans are superb pattern recognizers and a picture is worth at least a thousand words.
A growing shortage of data analysis talent, Data Scientists, is creating a serious constraint on the ability of businesses to capitalize on increases in big (and small) data sources. Data scientists using visual analytics can explore this data to extract meaningful and useful information and knowledge. Once extracted, this information can be communicated to stakeholders in ways that they understand. Visual analytics plays a crucial role in this analysis and communications process. It will bridge the gap between the data and analysts and stakeholders by providing techniques and tools to visually explore the data and then convey the stories found.
Professionals who can manage analytics and ‘big data’ are highly sought after by companies throughout the world. VIVA has developed training courses about visual analytics that incorporate lectures, discussions, seminars and hands-on laboratory components. These components allow participants to gain understanding of the basic techniques, tools and benefits of VA, to discover how to apply this basic knowledge during in-depth, hands-on experiences with current VA tools and techniques, and to learn how VA can be deployed in their organization. Our advanced courses provide trainees with an opportunity to identify, perform, interpret and utilize key analytics results using real-world data sets and to understand the role of big data and predictive visual analytics across multiple domains and industries.
Visual analytics brings together scientific and technical communities from computer science, information visualization, cognitive and perceptual sciences, interactive design, graphic design, and social sciences (Thomas & Cook, 2005).
Stefan Storey, Sensible Building Science
We use visual analytics to help clients to understand the key characteristics of building energy, to show them where they can save on their utility costs and drive down their GHG emissions.
Leah Macfadyen, Evaluation and Learning Analytics (UBC Faculty of Arts)
Visual analytics offers a fast and intuitive approach to exploring and analyzing all kinds of data sets ... It has also turned out to be a really powerful way to engage my very broad audience of educators and decision-makers.
Conny Lin, Rosetta Stone
[We use visual analytics for] exploratory analysis, real-time monitoring, presenting findings to stakeholders, presenting findings in conferences, and in scientific publications.
Ahmad Yaghoobi, Boeing
We find that tracking and visibility, causal chain analysis, hypothesis testing and detecting anomalies are well suited for advanced visual analytics tools that allow interactive exploration and assessment of complex data.