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Week 10 Term paper
Mobile Computing and Social Networks

Arnechia Washington
Professor Durgin
CIS500 Info Syst Decision-Making
March 16, 2014 When a business is looking at its online strategy these days, it shouldn’t confine itself to the world of computers. Instead, it needs to be thinking about how it can get into its customers’ pockets. Trends are pointing to the inevitable fact that mobile computing, and the Web site and applications that follow, holds great promises for business. The engine powering the gold rush onto mobile is the promise of geolocation, which is the ability for your phone to relay the information about where you are. The geolocation information in turn makes advertising on your phone smarter, since it can target you on a block-by-block basis. This technology has become one of the most popular trends in social networking giving us the ability to let our friends know where we are, identify popular or convenient places close to our physical location or even remotely check in to restaurants. These types of applications when accessed on a desktop system are bland and less of an experience. While there are some limitations to the scope of data that can be accessed and delivered to a mobile, equally there are a host of features, be it GPS or barcode scanning, which can open up new possibilities for how mobiles can deliver a fast, efficient and dynamic user experience. CPU performance tends to be more limited on mobile phones but it’s not about developing ‘desktop-lite’ versions of an application, it’s more about working with the innate advantages that the mobile device offers to create new ways of working and more innovative processes. Taking desktop applications to mobile devices demands a fresh approach; issues ranging from variations in screen size, multi-handset platforms, back-end connectivity and associated challenges such as performance, are signaling a new era of innovation in development.

References
“Advantages and



References: “Advantages and Disadvantages of Data Mining.” (n.d.). Retrieved from http://www.zentut.com/data-mining/advantages-and-disadvantages-of-data-mining/ Bose, Amitabh. Predictive analytics leads to better sales results, (n.d.). Retrieved from http://www.slideshare.net/WNSGlobalServices/predictive-analytics-helps-you-predict-customer-behavior “Think Before You Dig: Privacy Implications of Data Mining & Aggregation.” (September 2004). Retrieved from http://www.nascio.org/publications/documents/NASCIO-dataMining.pdf Tiwari, Sonal. The Usage Mining Framework for Business Intelligence, (September 2011). Retrieved from http://www.ijecct.org/v1n1/4.pdf “Why Predictive Analytics Is A Game-Changer.” (April 2010). Retrieved from http://www.forbes.com/2010/04/01/analytics-best-buy-technology-data-companies-10-accenture.html

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