Big Data Rewards

997 Words 4 Pages
As our society has progressed, we have adopted the mindset of “the bigger the better”. This is reflected in the houses we own, the food we consume, and the salaries that we hope to earn. In the recent past there has been an industry that has also begun to adapt this philosophy through data collection. The term “big data” has become a buzzword in numerous industries to refer to the large amount of data that is being stored, analyzed, and reported on in the world today. Many individuals have become enraptured with this phenomenon, this possibly includes those who are enrolled in this course. While interest in this field is growing and “big data” has shown to sometimes reap huge rewards, it is urged that individuals who interact with “big …show more content…
However, this automatically places smaller companies and businesses at a disadvantage. Smaller companies are at a disadvantage to compete on the “big data” forefront because usually they are lacking the resources that large institutions have access to. Many critiques argue that big data is not worth the investment because the reward does not outweigh the cost. However, there have been some miraculous breakthroughs and discoveries which have been aided by the use of big data (Scudellari, 2014). Smaller businesses and companies very rarely are even given this opportunity for success because they cannot foot the big bill of paying to collect and analyze the data. The use of big data can be a useful tool for companies and businesses to successfully compete in an industry. In my opinion, we should critically examine if it will lead to further disparities between successful and unsuccessful …show more content…
As a society we have more information now than ever before, which can create a paralyzing effect of not knowing where to begin. We may assume that because we have so much information available we are more informed than ever before. However, if a business were to make this assumption, it could cause a fatal error. Just because a business has a plethora of information on its clients does not mean that the conclusions that are being drawn from the data are accurate. For example in 2009 Google credited themselves with being able to diagnosis individuals with the flu faster than the CDC (Davis & Marcus, 2014). Google’s error in this situation is an important reminder that the relationships that are being studied through data analysis reflect correlation and not causation (Harford, 2014). It can be easy to slip into the mindset that because data analysis relies heavily on numbers and statistics that the conclusions from the analysis are causations, but that just is not true. There is no doubt that big data has the ability to use science and analytics in a very powerful and applicable way to bring to the surface certain relationships that otherwise would not have been thought of. However, it is imperative that the individuals who are interpreting the results of data analysis continue to view the output with a critical lens. To fall into the trap of accepting the results as fact or even worse as

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