Big Data: Bringing Meaning to Social Minutia


By Frank J. Ohlhorst

The amount of data created on a daily basis is reaching mind-numbing proportions, with social media posts and other trivial entries becoming a significant portion of the daily storm of digital data. While many treat social media as little more than gossip, inane blathering and information that matters to only a small group of individuals, the truth of the matter is all that minutia may have value.

Nevertheless, the real trick is how to uncover that value--to make any sense out of the numerous tweets, Facebook posts, and other bits of social information. The path to “making sense” can be paved with big data technologies that are starting to come into vogue for businesses large and small. It is truly the processes that make up big data analytics that can deliver answers and drive business processes.

It may not be so easy to see how big data analytics can garner value out of social minutia. However, big data analytics has the muscle to plow through the enormous realm of Facebook, the twitterverse and numerous other worlds of social interactions. After all, big data analytics is all about mining information from huge piles of data.

Nevertheless, value is a subjective element. Simply put, when mining for gold, you have to know what gold is--and isn’t. That said, the tools that make up big data analytics have limitations and a human touch is needed to make sense out of all the noise. The trick is to know what to look for. Arguably, business marketing and product development has the most to gain from applying big data analysis to social data sources. Those business processes can benefit from customer sentiment analysis, product adoption trends and common complaints that float around in the ether.

Big data analysis can focus on mining social media data sets for keywords, such as a product or company, and then cross referencing all occurrences to that mention to create a sentiment index, which can lead to invaluable insights. While it may sound simple, the truth is it is anything but simple. Businesses will need to turn to data scientists and others to really make big data analytics work for them. And, of course, they will have to educate themselves on how big data works.

Frank J. Ohlhorst is a technology journalist, author, professional speaker, and IT business consultant with more than 25 years of experience in the technology arena. His latest book, Big Data Analytics: Turning Big Data into Big Money, offers valuable insights into the realm of big data is available at http://amzn.to/T33yh4.



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