Visual Analytics

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Visual Analytics

Visual Analytics

Visual Analytics


Over the past few years, the use of visual analytics tools has become much common in the organizations, mainly for the purposes of data gathering and analysis. Using visual analytics improve the organization's capabilities of research gathering and analyzing significantly. The interactive visual interfaces used in this field provide the users or organizations with clear understanding of the topics. There are various ways for which visual analytics has been applied; for example, these tools are used for gathering data from stock markets or analyzing the data collected as a result of survey conducted. This paper describes the current research and applications of visual analytics.

What is Visual Analytics

Visual analytics can be very simply defined as the science of analytical reasoning. This field is highly supported by the use of interactive visual interfaces. The problems which are otherwise impossible to analyze by the human due to the size, and complexity level become a piece of cake with the effective use of visual analytics tools (Kosara, 2007). The concepts of visual analytics are driven from various subject areas such as knowledge management, cognitive science, statistical analysis, and decision science. Due to the influence of many subjects on visual analytics, it is often said that it is made up of a multitude of different systems. With the use of visual analytics in the areas of science and technology, the efficiency of aspects such as analytical reasoning, data transformations, computation and visualization, technology transition and analytic reporting improves significantly. The major reason due to which visual analytics minimizes the distance between human and information is the use of innovative theory and computational based tools; these tools are mainly designed based on the concepts of design, cognitive and perceptual principles. The two major uses of visual analytics tools are prediction and understanding.

It must be noted that to apply visual Analytics is far more complex than people think. It is not as simple as collecting data and applying visual analysis tool on it; rather there is a need to choose the analytical method as well. Analytical techniques are a necessary part of the visual analytics tools. Due to the presence of analytical techniques, the user becomes able to create the scenarios and hypotheses. The analytical techniques help the analyst in determining any hidden relationships in the datasets, which often lead to providing deeper insights about the data. in addition, the visual analysis tools also make the information available to other users, which they can use in the future analysis applications.

Applications of Visual Analytics tools

Visual analytics applications provide the users with various ways to analyze the data. These tools can even be used for creating new systems. This section includes examples to describe the ways in which researcher have been applying the visual analytics tools currently.

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