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Data visualization or data visualisation is viewed by many disciplines as a modern equivalent of visual communication. It is not owned by any one field, but rather finds interpretation across many (e.g. it is viewed as a modern branch of descriptive statistics by some, but also as a grounded theory development tool by others). It involves the creation and study of the visual representation of data, meaning "information that has been abstracted in some schematic form, including attributes or variables for the units of information". Topics like Data warehousing, data pre-processing , Machine learning .
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Scope and Importance :
A primary goal of data visualization is to communicate information clearly and efficiently to users via the statistical graphics, plots, information graphics, tables, and charts selected. Effective visualization helps users in analyzing and reasoning about data and evidence. It makes complex data more accessible, understandable and usable. Users may have particular analytical tasks, such as making comparisons or understanding causality, and the design principle of the graphic (i.e., showing comparisons or showing causality) follows the task. Tables are generally used where users will look-up a specific measure of a variable, while charts of various types are used to show patterns or relationships in the data for one or more variables.
Data visualization is both an art and a science. The rate at which data is generated has increased, driven by an increasingly information-based economy. Data created by internet activity and an expanding number of sensors in the environment, such as satellites and traffic cameras, are referred to as "Big Data". Processing, analysing and communicating this data present a variety of ethical and analytical challenges for data visualization. The field of data science and practitioners called data scientists have emerged to help address this challenge.
The Machine learning market has been achieving strong revenues. The Global Market Statistics shows that it has reached a revenue height of 9.15USD (billion), 6.15 USD (billion) and 5.12 USD (billion) for services, hardware and software, respectively for the year 2013. The global market statistic also shows a revenue forecast for the global big data market from 2011 to 2017. For 2016, the source projects the global big data market is predicted to grow to more than 45 billion U.S. dollars in revenue.
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This page was last updated on 12th Sep, 2015
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