The world has become like one large computer with billions of data entry points spread across all continents. Humans of all walks of life passively feed gigantic amounts of data into this system on an hourly basis as they go about their daily activities. A shopper in the US who buys a certain item online feeds some data as a smartphone user in Papua New Guinea who likes an item online is doing the same. The concept of big data was developed after the great depression of 2008 and entails experts and global corporations seeking to collect and analyze these gigantic amounts of data so as to derive inferences, trends, and preferences (Drenik, 2014) . Big data has, therefore, become a major sensation in the world as the source of research material. There is a direct proportion relationship between cost and accuracy in the big data sector, which creates a quagmire about its viability.
One of the biggest advantages of big data as a research tool is its high capacity for honesty as opposed to surveys. It has now been established that mankind is actively and/or passively dishonest, more so when questioned about personal issues due to a desire to maintain appearances. It is for this same reason that sociologists prefer ethnography to conducting surveys. With big data, the sampled individuals will not even be aware that they are being sampled (Drenik, 2014) . This will cause them to act naturally and, therefore, honestly. The opinions that people express when they do not know that anyone secondary is listening will more often than not be the raw truth. The second advantage of big data is the variety of both the data and the data source. Big data can enable a researcher to understand the opinion about an almost infinite number of subjects drawn from virtually all over the world. This is because billions of people use computerized devices from virtually all the countries in the world (Drenik, 2014) . This makes for a very wide field.
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The primary disadvantage of big data is the cost implications. Research has shown that about 2.5 quintillion bits of data are produced every day and from different sources. The data is in multimedia format, multilingual and spread across a geographical area that covers the entire globe. For the data to be analyzed. It needs to be collected and stored. The kind of a system that can store this amount of data is expensive to acquire, operate, and maintain. Even if a researcher was to decide to only store and analyze a segment of data, there is still the issue of a system that can select that specific segment from the mountain of raw data (Drenik, 2014) . Further, for any level of accuracy to be achieved in the analysis of big data, a high level of expertise, coupled with expensive systems must be involved. The second major disadvantage of raw data lies in the fact that it is a new yet very rapidly evolving field, a fact that creates a high level of known and unknown contingencies. The key to research is understanding the system being used to as to eliminate variables within it, leaving variables only in the data itself (Columbus, 2016) . When a researcher is trying to analysis both data and the system itself, accuracy is diminished .
One of the most exciting uses of big data by businesses is in the advertising and branding aspect of marketing. The modern marketing regimen has proven that the nature and quality of a product have little to do with how much sales it generates. Instead, it is the opinion of the consumers about the product that drives sales. The key to modern branding is not to make the customers want to hear about the product but rather make the product sound like what the customers want to hear (Columbus, 2016) . Big data will enable businesses to understand beforehand what their customers want to hear then create their marketing regimens around it.
References
Columbus, L. (2016, May 09). Ten ways big data is revolutionizing marketing and sales. Retrieved July 17, 2017, from https://www.forbes.com/sites/louiscolumbus/2016/05/09/ten-ways-big-data-is-revolutionizing-marketing-and-sales/#16ff81821cff
Drenik, G. (2014, May 05). Is mass hysteria driving the big data market? Retrieved July 17, 2017, from https://www.forbes.com/sites/prospernow/2014/05/05/is-mass-hysteria-driving-the-big-data-market/#e5c38bb40e02
