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Contents contributed and discussions participated by Tanner B

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Tanner B

Visual Business Intelligence - Microsoft Excel's Idea of Visual Data Analysis - 0 views

www.perceptualedge.com/blog

visual data analysis

shared by Tanner B on 30 Mar 10 - Cached
  • No software product is used more than Microsoft Excel for the analysis and presentation of quantitative data.
  • Nevertheless, it is fair to say that you can use Excel to present data effectively, but within severe limits, and only if you’re willing to work around its problems.
  • To say it can be used for visual data analysis, however, is a stretch that exceeds its reach. To date, Excel is at best an infant in the world of visual data analysis, barely able to roll over.
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  • Those of you who are familiar with visual data analysis and what good software does to support it will find Microsoft’s notion of visual data analysis entertaining. I invite you to watch Microsoft’s demo and let me know what you think of it.
Tanner B

Visual Data Analysis, Scientific Computing - 0 views

www.scientificcomputing.com/visual-data-analysis.aspx

visual data analysis

shared by Tanner B on 30 Mar 10 - No Cached
  • Visual Data Analysis (VDA) tool packages are powerful software tools that allow the development of complex solutions to visualize and analyze data.
  • The imaging features of a VDA package are often the most tangible aspect of the tool, but the overall effectiveness of a package is really based on its data manipulation and analysis capabilities.
  • A robust and flexible VDA tool should contain a broad range of mathematical, statistical and data manipulation capabilities, which are seamlessly tied to the visualization components through a high-level array-based scripting language.
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  • Support for popular formats (XML, CDF, HDF, binary, ASCII, TIF) should be included in the base product, and services for customized data handlers should be available through the provider.
  • There are several factors that determine or impact performance, including use of pre-built data manipulation functions, limitations on data set size, parallelization, supported data types, and performance of the package's algorithms.
  • In general, the best performers will be the packages that support a broad range of data types, thus minimizing impact on memory requirements; support parallelization technology such as OpenMP; and have kernels optimized for visual data analysis.
  • Various techniques, solutions, and products are available on the market to visually analyze data, but few offer a full spectrum of visualization capabilities coupled with sufficient complementary analytical functionality.
  • In conclusion, a careful evaluation of key VDA tool characteristics, with the end solution in mind, should factor into the selection process to include the combined functionality, reliability, scalability, performance and portability of a VDA tool.
Tanner B

Wondering what cool new technologies are on the Horizon? | Technology for Tea... - 0 views

wp.wpi.edu/...horizon-2010

visual data analysis

shared by Tanner B on 30 Mar 10 - No Cached
  • Data analysis is at the heart of many science and engineering fields, and so it is a topic of great interest here at WPI.  Visual data analysis is a field that uses modeling techniques to represent large data sets visually allowing the user or users to search for patterns and structures within the data.  Many visual data analysis tools are also on the horizon that will aid users in their data mining process.
Tanner B

2010 Horizon Report » Four to Five Years: Visual Data Analysis - 0 views

wp.nmc.org/...visual-data-analysis

visual data analysis

shared by Tanner B on 30 Mar 10 - Cached
  • Visual data analysis blends highly advanced computational methods with sophisticated graphics engines to tap the extraordinary ability of humans to see patterns and structure in even the most complex visual presentations.
  • Data collection and compilation is no longer the tedious, manual process it once was, and tools to analyze, interpret, and display data are increasingly sophisticated, and their use routine in many disciplines.
  • In advanced research settings, scientists and others studying massively complex systems generate mountains of data, and have developed a wide variety of new tools and techniques to allow those data to be interpreted holistically, and to expose meaningful patterns and structure, trends and exceptions, and more.
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  • Researchers that work with data sets from experiments or simulations, such as computational fluid dynamics, astrophysics, climate study, or medicine draw on techniques from the study of visualization, data mining, and statistics to create useful ways to investigate and understand what they have found.
  • The blending of these disciplines has given rise to the new field of visual data analysis, which is not only characterized by its focus on making use of the pattern matching skills that seem to be hard-wired into the human brain, but also in the way in which it facilitates the work of teams working in concert to tease out meaning from complex sets of information.
  • it possible for almost anyone with an analytical bent to easily interpret all sorts of data
  • Many are free or very inexpensive, bringing the ability to engage in rich visual interpretation to virtually anyone.
  • Online services such as Many Eyes, Wordle, Flowing Data, and Gapminder accept uploaded data and allow the user to configure the output to varying degrees.
  • By manipulating variables, or simply seeing them change over time (as Gapminder has done so famously) if patterns exist (or if they don’t), that fact is easily discoverable.
  • The promise for teaching and learning is further afield, but because of the intuitive ways in which it can expose complex relationships to even the uninitiated, there is tremendous opportunity to integrate visual data analysis into undergraduate research, even in survey courses.
  • Visual data analysis may help expand our understanding of learning itself. Learning is one of the most complex of social processes, with a myriad of variables interacting in highly complex ways, making it an ideal focus for the search for patterns.
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