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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 ...
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]
Interactive Visual Analysis is an iterative process. Discoveries made after brushing of the data and looking at the linked views can be used as a starting point for repeating the process, leading to a form of information drill-down. As an example, consider the analysis of data from a simulation of a combustion engine.
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. The data may also be collected from sensors in the environment, including traffic cameras, satellites, recording devices, etc.
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]
The process of data wrangling may include further munging, data visualization, data aggregation, training a statistical model, as well as many other potential uses. Data wrangling typically follows a set of general steps which begin with extracting the data in a raw form from the data source, "munging" the raw data (e.g. sorting) or parsing the ...
Data visualization is a related subcategory of visualization dealing with statistical graphics and geospatial data (as in thematic cartography) that is abstracted in schematic form. [ 7 ] Information visualization concentrates on the use of computer-supported tools to explore large amount of abstract data.
The multivariate data that is the original input for any grand tour visualization is a (finite) set of points in some high-dimensional Euclidean space. This kind of set arises naturally when data is collected. Suppose that for some population of 1000 people, each person is asked to provide their age, height, weight, and number of nose hairs.