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Data presentation architecture weds the science of numbers, data and statistics in discovering valuable information from data and making it usable, relevant and actionable with the arts of data visualization, communications, organizational psychology and change management in order to provide business intelligence solutions with the data scope ...
Exploratory data analysis is a technique to analyze and investigate a dataset and summarize its main characteristics. A main advantage of EDA is providing the visualization of data after conducting analysis. Tukey's championing of EDA encouraged the development of statistical computing packages, especially S at Bell Labs. [4]
Data visualization uses information displays (graphics such as, tables and charts) to help communicate key messages contained in the data. [46] Tables are a valuable tool by enabling the ability of a user to query and focus on specific numbers; while charts (e.g., bar charts or line charts), may help explain the quantitative messages contained ...
Data exploration can also refer to the ad hoc querying or visualization of data to identify potential relationships or insights that may be hidden in the data and does not require to formulate assumptions beforehand. [1] Traditionally, this had been a key area of focus for statisticians, with John Tukey being a key evangelist in the field. [5]
Orange is a component-based visual programming software package for data visualization, machine learning, data mining, and data analysis. Orange components are called widgets. They range from simple data visualization, subset selection, and preprocessing to empirical evaluation of learning algorithms and predictive modeling.
Visual analytics seeks to marry techniques from information visualization with techniques from computational transformation and analysis of data. Information visualization forms part of the direct interface between user and machine, amplifying human cognitive capabilities in six basic ways: [2] [5]
Jeffrey Michael Heer (born June 15, 1979) is an American computer scientist best known for his work on information visualization and interactive data analysis.He is a professor of computer science & engineering [1] at the University of Washington, where he directs the UW Interactive Data Lab. [2] He co-founded Trifacta with Joe Hellerstein and Sean Kandel in 2012.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]