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Data visualization or data visualisation is 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".
According to Friedman (2008) the "main goal of data visualization is to communicate information clearly and effectively through graphical means. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often fail to achieve a balance between form and function, creating gorgeous data visualizations which fail to serve their main purpose — to communicate information".
Data visualization is closely related to information graphics, information visualization, scientific visualization, and statistical graphics. In the new millennium, data visualization has become an active area of research, teaching and development. According to Post et al. (2002), it has united scientific and information visualization. Brian Willison has demonstrated that data visualization has also been linked to enhancing agile software development and customer engagement.
KPI Library has developed the “Periodic Table of Visualization Methods,” an interactive chart displaying various data visualization methods. It includes six types of data visualization methods: data, information, concept, strategy, metaphor and compound.
There are different approaches on the scope of data visualization. One common focus is on information presentation, such as Friedman (2008) presented it. In this way Friendly (2008) presumes two main parts of data visualization: statistical graphics, and thematic cartography. In this line the "Data Visualization: Modern Approaches" (2007) article gives an overview of seven subjects of data visualization:
All these subjects are closely related to graphic design and information representation.
For different types of visualizations and their connection to infographics, see infographics.
Data acquisition is the sampling of the real world to generate data that can be manipulated by a computer. Sometimes abbreviated DAQ or DAS, data acquisition typically involves acquisition of signals and waveforms and processing the signals to obtain desired information. The components of data acquisition systems include appropriate sensors that convert any measurement parameter to an electrical signal, which is acquired by data acquisition hardware.
Data analysis is the process of studying and summarizing data with the intent to extract useful information and develop conclusions. Data analysis is closely related to data mining, but data mining tends to focus on larger data sets with less emphasis on making inference, and often uses data that was originally collected for a different purpose. In statistical applications, some people divide data analysis into descriptive statistics, exploratory data analysis, and inferential statistics (or confirmatory data analysis), where the EDA focuses on discovering new features in the data, and CDA on confirming or falsifying existing hypotheses.
Types of data analysis are:
Data governance encompasses the people, processes and technology required to create a consistent, enterprise view of an organisation's data in order to:
Data management comprises all the academic disciplines related to managing data as a valuable resource. The official definition provided by DAMA is that "Data Resource Management is the development and execution of architectures, policies, practices, and procedures that properly manage the full data lifecycle needs of an enterprise." This definition is fairly broad and encompasses a number of professions that may not have direct technical contact with lower-level aspects of data management, such as relational database management.
Data mining is the process of sorting through large amounts of data and picking out relevant information. It is usually used by business intelligence organizations, and financial analysts, but is increasingly being used in the sciences to extract information from the enormous data sets generated by modern experimental and observational methods.
It has been described as "the nontrivial extraction of implicit, previously unknown, and potentially useful information from data" and "the science of extracting useful information from large data sets or databases." In relation to enterprise resource planning, according to Monk (2006), data mining is "the statistical and logical analysis of large sets of transaction data, looking for patterns that can aid decision making".
Data transforms is the process of Automation and Transformation, of both real-time and offline data from one format to another. There are standards and protocols that provide the specifications and rules, and it usually occurs in the process pipeline of aggregation or consolidation or interoperability. The primary use cases are in integration systems organizations, and compliance personnels.
|Amira||GUI/Code Data Visualization||Scientists||Proprietary|
|Avizo||GUI/Code Data Visualization||Engineers, Scientists||Proprietary|
|Cave5D||Virtual Reality Data Visualization||Scientists||Open Source|
|Data Desk||GUI Data Visualization||Statistician||Proprietary|
|Datawatch||GUI Data Visualization||Business Users||Proprietary|
|DAVIX||Operating System with data tools||Security Consultant||Various|
|Dundas Data Visualization, Inc.||GUI Data Visualization||Business Managers||Proprietary|
|ELKI||Data mining visualizations||Scientists, Teachers||Open Source|
|Eye-Sys||GUI/Code Data Visualization||Engineers, Scientists||Proprietary|
|Ferret Data Visualization and Analysis||Gridded Datasets Visualization||Oceanographers, Meteorologists||Open Source|
|Gephi||GUI Data Visualization||Statisticians||Open Source|
|GGobi||GUI Data Visualization||Statisticians||Open Source|
|ggplot2||Data visualization package for R||Programmers||Open Source|
|Grapheur||GUI Data Visualization||Business Users, Project Managers, Coaches||Proprietary|
|High-D||GUI Data Visualization||Engineers, Scientists||Proprietary|
|IBM OpenDX||GUI/Code Data Visualization||Engineers, Scientists||Open Source|
|IDL (programming language)||Programming Language||Programmers||Open Source|
|Improvise||Library and GUI Data Visualization||Programmers/designers (building), Analysts (browsing)||Open Source|
|Infragistics||Data Visualization Controls for iOS, Android, Windows Phone, .NET, jQuery||Software Development (UI/UX), Mobile Application Developers, Web Developers||Proprietary|
|Instantatlas||GIS Data Visualization||Analysts, Researchers, Statisticians, GIS Professionals||Proprietary|
|Keyzo IT Solutions Ltd.||Data Visualization Software||Software Development||Proprietary|
|MeVisLab||GUI/Code Data Visualization||Engineers, Scientists||Proprietary|
|MindView||Mind Map Graphic Visualization||Business Users, Project Managers||Proprietary|
|Mondrian||GUI Data Visualization||Statistician||Open Source|
|Panopticon Software||Enterprise application, SDK, Rapid Development Kit (RDK)||Business Users||Proprietary|
|Panorama Software||GUI Data Visualization||Business Users||Proprietary|
|ParaView||GUI/Code Data Visualization||Engineers, Scientists||BSD|
|Processing (programming language)||Programming Language||Programmers||GPL|
|protovis||Library / Toolkit||Programmers||BSD|
|qunb||GUI Data Visualization||Non-Expert Business Users||Proprietary|
|R (programming language)||Programming Language||Scientists, Researchers, Statisticians, Programmers||GPL|
|SAS Institute||GUI Data Visualization||Business Users, Analysts||Proprietary|
|Science of Science Tool (Sci2)||GUI/Code Data Visualization, Network Analysis, Data Mining||Scientists, Researchers, Programmers, Students||Open Source|
|Smile (software)||GUI/Code Data Visualization||Engineers, Scientists||Proprietary|
|Spotfire||GUI Data Visualization||Business Users||Proprietary|
|StatSoft||Company of GUI/Code Data Visualization Software||Engineers, Scientists||Proprietary|
|Tableau Software||GUI Data Visualization||Business Users||Proprietary|
|The Hive Group: HiveOnDemand||GUI Data Visualization||Business Users, Academic Users||Proprietary|
|The Hive Group: Honeycomb||GUI Data Visualization||Business Users, Engineers||Proprietary|
|TinkerPlots||GUI Data Visualization||Students||Proprietary|
|Tom Sawyer Software||Data Visualization and Social Network Analysis Applications||Business Users, Engineers, Scientists||Proprietary|
|Trade Space Visualizer||GUI/Code Data Visualization||Engineers, Scientists||Proprietary|
|TreeMap||GUI Data Visualization||Business Managers||Proprietary|
|Tulip||GUI Data Visualization||Researchers, Engineers||Open Source|
|Vis5D||GUI Data Visualization||Scientists||Open Source|
|VisAD||Java/Jython Library||Programmers||Open Source|
|Visifire||Library||Programmers||Was Open Source, now Proprietary|
|VisIt||GUI/Code Data Visualization||Engineers, Scientists||BSD|
|VTK||C++ Library||Programmers||Open Source|
|Yoix||Programming Language||Programmers||Open Source|
|The topic of this article may not meet Wikipedia's notability guideline for neologisms. (August 2010)|
|This article needs additional citations for verification. (March 2010)|
Data presentation architecture (DPA) is a skill-set that seeks to identify, locate, manipulate, format and present data in such a way as to optimally communicate meaning and proffer knowledge.
Historically, the term data presentation architecture is attributed to Kelly Lautt: "Data Presentation Architecture (DPA) is a rarely applied skill set critical for the success and value of Business Intelligence. 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, delivery timing, format and visualizations that will most effectively support and drive operational, tactical and strategic behaviour toward understood business (or organizational) goals. DPA is neither an IT nor a business skill set but exists as a separate field of expertise. Often confused with data visualization, data presentation architecture is a much broader skill set that includes determining what data on what schedule and in what exact format is to be presented, not just the best way to present data that has already been chosen (which is data visualization). Data visualization skills are one element of DPA."
DPA has two main objectives:
With the above objectives in mind, the actual work of data presentation architecture consists of:
DPA work has some commonalities with several other fields, including:
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