andrew
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
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
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.