andrew

Topics: Data analysis, Data, Data mining Pages: 10 (2683 words) Published: December 8, 2014


TUI UNIVERSITY
Andrew Springstead
Module 1 CS: Information Networking as Technology: Tools, Uses, and Socio-Technical Interactions ITM501: Management of Information Systems and Business Strategy Dr. Mary Lind
June 17, 2014

Information Overload
“Are organizations likely to find better solutions to information overload through changes to their technical systems or their social systems -- or both? Why?” To answer this question, this paper will discuss the technical and social systems of companies specifically based on review of the articles by Blair, Bellinger, et al, Green, and Liu and Errey as well as other information on related data companies such as Amazon and SAS. The context of the paper will aide in the understanding of an ideal way to process the information present in the market and then use it for company benefits. This paper will also review and analyze the importance of info-tsunami in context of specific markers and give specific examples on how data storage and analysis is now the latest trend in the market. Various big data softwares present in the market and comment on the future trends of the market will be reviewed. Finally, I will propose an answer to the original question posed of what betterment is most important in dealing with information overload social systems, technological systems, or both? History of Data Mining/Sharing

In order to truly understand information overload and how to deal with it, we must start by analyzing various aspects of data starting from its history through the current and probable future trends of the market. Today there are zillions of pieces of data in the market growing for over 30% per year bases (Blair, 2010). The roots of the big data come from ancient days when people used to huge manuscripts and biblical resources to pass on the knowledge of present generation to the next one. They not only documented information, but also backed up or made it easier to share that information by creating duplicates of the original work. People with different philosophies discussed the same issues with a different context and vision to give alternate versions of the existing issues. However, this increase in the amount of information collected led to what may have appeared to be an unsurmountable collection that could not be fully read in an acceptable amount of time or never being able to find specific information, which could be described as an information overoad (Blair, 2010). People would have too much information to sift through to find what they needed, which would need to lead to an evolution in that form of data storage such as different note-taking capabilities as well as organization (Blair, 2010). Note-taking capabilities enabled the researchers to organize the structure of different ancient texts and later on printing evolved the structure of writing as indexes and bibliographies became norm for the research papers, which helped people to find the specific information they were looking for or the source of more information. Encyclopedias were created to serve as a set of easily accessible and searchable information on a broad amount of topics. Also, the advent of the Dewey Decimal System meant that a lot of general information could be found in a short amount of time. The Dewey Decimal Classification initially sorts information into 10 categories, and then into another 100 sub-categories, giving you 1, 000 specific categories to search (University Library, n.d.). For example, you could search the 600’s for Technology or Applied Sciences categories and find sub-category (also known as a “call number”) 621 and search specifically for Applied Physics (University Library, n.d.). All of these things lead to less of a feeling of information overload as people did not need to spend a lifetime searching for the data that they needed. However, personal collection of information would take up large amounts of space. Fast forward time a...

References: The Apache Software Foundation. (2014). Welcome to Apache Hadoop! Retrieved from http://hadoop.apache.org/.
The MathWorks, Inc. (2014). Time Series Regression VI: Residual Diagnostics. Retrieved from http://www.mathworks.com/help/econ/examples/time-series-regression-vi-residual-diagnostics.html.
Muenchen, R. (2014). The Popularity of Data Analysis Software. r4stats.com. Retrieved from http://r4stats.com/articles/popularity/.
Marinescu, D. (2013). Cloud Computing: Cloud Vulnerabilities. TechNet Magazine, July 2013. Retreived from http://technet.microsoft.com/en-us/magazine/dn271884.aspx.
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