Creating Value of Social Minutia With Big Data


Social Networks are generating vast amounts of data, which leaves many to ponder over the idea whether the data being generated has some intrinsic value or is it just loads of loud noise.

The amount of data being generated on a daily basis is actually quite mind numbing, especially with social media posts and various other trivial entries which are becoming a significant portion of the Big Data set.

Although, many of us treat social media a gossip spots for inane blathering consisting of information that only matters to a particular group, the truth of the matter is that all of the minutia might actually have value. Nonetheless, the real trick here is to actually understand and decipher information that has value by filtering all of the wheat from the chaff, while trying to make sense out of the large amounts of Facebook posts, Tweets and various other bits of information that are just floating around in the social ether.

The path towards “making sense” of all that clutter can be deciphered by technologies that have recently gained popularity among small and large enterprises known as “Big Data”. However, it’s not the generic term “Big Data” that provides value, it’s actually the processes that make up the Big Data Analytics that provide us with answers that drive and enhance business processes.

It’s not easy to see how Big Data Analytics can provide you will great value from the minutia floating around the social ether, but the elements that form the Big Data Analytics actually have the muscles and strength to plow through the Facebook realm, the Twitter-universe and various other social interaction sites. After all, the basic function of the Big Data Analytics is based on mining through huge piles of generic data.

Nonetheless, the value created is a subjective element; think about it, if you decide to go mining for gold, you obviously need to know what gold is in order to begin. With that said, the tools used to form the Big Data Analytics do have their own limitations, so human touch is definitely required to make any sense of all that “clutter”. The trick here is to know what you’re looking for. It’s still highly debatable, but product development and business marketing are the two main areas that have the most to gain when applying Big Data Analysis with Social Data sources.

These are the business processes that can actually benefit from common complaints, product adoption trends and customer sentiment analysis that are floating around in the social realm. The process that can focus on mining through social media data searching for keywords like company name or product name and then cross reference them with occurrences in the social realm can create a sentiment index which will help in providing insights for businesses.

Although, it sounds simple, it’s far from it. Businesses will have to turn towards data scientists and other data analysts to really understand the dynamics of the Big Data Analytics and of course educate themselves on how Big Data functions, that’s if they want to be successful.

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