An Organization Map Technology For Big Data

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The internet has changed the ways in which data can be collected and more importantly, it has changed the amount of data available (Grover, 2014). Social behaviors, networking behaviors and information sharing are providing organizations with volumes of data and there is a need to be able to understand, manage and define all of the information. This trend of voluminous data is known as, “big data.” According to the International Journal of Computer and Electronics Research, in 2014, there is no extensive reference architecture currently available for big data (Grover, 2014). Several small scale data architectures exist, but most are limited in scope or missing the functional views which help an organization map technology to function…show more content…
Therefore, information asymmetry is an issue for consumers and supply chains when interoperable data does not align. This exists because one party (either the buyer or producer) has less than perfect information than the other. According to an article by Information and Technology Management, a great deal of information asymmetry exists in the coffee supply chain. This article describes the data incompatibility between small and medium coffee farmers, roasters, and traders. Producers (coffee farmers) are usually a cooperative of many small farmers and being able to gather documentation to identify the source and quality of the coffee is difficult (Sayogo, Zhang, Luna-Reyes, Jarman, Tayi, Lines-Andersen, Pardo, Andersen, 2015). Many farmers believe the data collection is not valuable and waste of their time and effort for many reasons. Including limited resources such as staff and technology, and information bias (competition based on too much information about the supply). Furthermore, the entire process is overly too difficult to perform in a uniformed way. Most important, this results in the farmers incurring additional costs to ensure data collection that they may not see a profit for later (Sayogo, Zhang, Luna-Reyes, Jarman, Tayi, Lines-Andersen, Pardo, Andersen, 2015). Therefore, incorrect or “assumed” information is collected to the best of the producer’s knowledge
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