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In business, data and information visualization can constitute a part of data storytelling, where they are paired with a coherent narrative structure or storyline to contextualize the analyzed data and communicate the insights gained from analyzing the data clearly and memorably with the goal of convincing the audience into making a decision or ...
To Tufte, good data visualizations represent every data point accurately and enable a viewer to see trends and patterns in the data. Tufte's contribution to the field of data visualization and infographics is considered immense, and his design principles can be seen in many websites, magazines, and newspapers today.
Tufte uses the term "data-ink ratio" to argue against using excessive decoration in visual displays of quantitative information. [15] In Visual Display, Tufte explains, "Sometimes decoration can help editorialize about the substance of the graphic. But it is wrong to distort the data measures—the ink locating values of numbers—in order to ...
McCandless is the founder of the visual blog Information Is Beautiful.Early explorations into the synergy between data visualisation and his work as a journalist led to the development of Information Is Beautiful [2] and the subsequent publication of his book of the same name (titled A Visual Miscellaneum in the United States).
Visual analytics is "the science of analytical reasoning facilitated by interactive visual interfaces." [2] It can attack certain problems whose size, complexity, and need for closely coupled human and machine analysis may make them otherwise intractable. [3]
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]
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Data science is an interdisciplinary academic field [1] that uses statistics, scientific computing, scientific methods, processing, scientific visualization, algorithms and systems to extract or extrapolate knowledge from potentially noisy, structured, or unstructured data.