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Data Visualization

Highlighting data visualization tools at James E. Brooks Library

Data Visualiztion

Raw data is often hard to use if we want to see trends or patterns. Data visualization helps us present and interpret data.

Data visualization (often abbreviated data viz^[1]) is an interdisciplinary field that deals with the graphic representation of data. It is a particularly efficient way of communicating when the data is numerous as for example a Time Series. From an academic point of view, this representation can be considered as a mapping between the original data (usually numerical) and graphic elements (for example, lines or points in a chart). The mapping determines how the attributes of these elements vary according to the data. In this light, a bar chart is a mapping of the length of a bar to a magnitude of a variable. Since the graphic design of the mapping can adversely affect the readability of a chart,^[2] mapping is a core competency of Data visualization. Data visualization has its roots in the field of Statistics and is therefore generally considered a branch of Descriptive Statistics. However, because both design skills and statistical and computing skills are required to visualize effectively, it is argued by some authors that it is both an Art and a Science.^{[3] (from Wikipedia)}

Tools for Data Visualization

ARC GIS
CorelDraw Graphics Suite
ERDAS Imagine
Excel
Spreadsheet software from microsoft
GeoDa
Google Earth Pro
QGIS
R
Statistix 10
Tableau
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Tableau works with numeric and categorical data to produce advanced graphics. Browse the Tableau public gallery to see examples of visuals and dashboards. The Datacruncher machine in the Data & GIS Lab has a Tableau license and a trial version of Tableau is available for download from the website.
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