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What Is Data Mining Visualization?

Article Details
  • Written By: D. Nelson
  • Edited By: M. C. Hughes
  • Last Modified Date: 18 October 2017
  • Copyright Protected:
    2003-2017
    Conjecture Corporation
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Data mining is the act of extracting important data from large amounts of information. In most cases, an objective of data mining is to discover new information regarding a subject from existing data. This process often requires specialists to pair sets of data and perceive information from new perspectives. A professional who practices data mining visualization uses graphs, charts, and other visual formats to convey information extracted through a data mining process.

Many experts believe that there are two important factors that can impact the success of a data mining visualization project: clarity and aesthetic appeal. Data mining visualization is effective when it conveys relevant information and a desired message. This means that visualization should present complex information in a clear and simplified manner.

Aesthetics are also important in data visualization. Many practitioners believe that effective visualization need not be boring. On the contrary, professionals may use colors, shapes, and textures that create an appealing presentation.

Professionals who practice data mining visualization use special software. These programs often are designed for particular industries. For example, an engineer may require visualization software that allows him or her to extract data from sets regarding properties of materials. An engineer then might create three-dimensional illustrations representative of a material.

Financial experts can use data mining visualization software that enable to them to organize data regarding market behaviors. They may extract data from different periods and markets to create charts that demonstrate trends and economic indicators. Executives and managers can use this information to reduce risk and increase confidence in investors and shareholders.

Information Technology (IT) professionals and web develops use data mining visualization. Programming languages often are visualized to offer programmers clear illustrations of how various commands interact. Web designers create charts that illustrate complex hyperlink networks.

Many maps used in geographic, sociological, and political contexts are results of data mining visualization. Maps that illustrate factors such as rates of employment or population growth often are generated on visualization software. Political analysts might use these maps to influence opinions of citizens or to convey important data to colleagues and staff members.

Professionals who specialize in optimizing data mining visualization systems categorize different methods of visualization. For example, some methods are most effective when used to provide process transparency. Some users may prefer methods that can provide overviews of a process or study, whereas others may prefer visualization methods that provide detail oriented illustrations. Convergent thinking and divergent thinking are other aspects of a data set that professionals illustrate through data visualization.

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