01/08/2014 10:49 am ET Updated Mar 10, 2014

How to Make Money With Big Data

The web is getting smarter. And just when the world begins to figure the internet out, it changes. The internet of a decade ago is nothing like today's version and today's version will be antiquated in the next five years. The reason -- big data.

Big data is a quickly tossed around term that is roughly translates to describe extremely large sums of complex data that avalanches the web daily. The measurements of this data is currently calculated in petabytes and exabytes (the latter equally a digit followed by 18 zeros)!

Furthermore, statistics show that the net will reach 1.3 zettabytes of data in 2016. However, all of this was predicted decades ago by data miners. They knew that huge sums of information would engulf the web and there would a market to find hidden gems in big data.

Before the advent of wikis and the dot-com bust, it was understood that big data was going to be a different animal. At the turn of the century, the addition of the net to economic markets was solidified and big data was beginning to take on a form. Speaking about the adolescent years of the web, Rich Spitzer of TrendPointers, Inc. relates, "There was a trajectory of information circulating; it was the old connect-the-dots. We were looking to speed up the availability of information and we were working on harvesting that type of news in every measure that comes out. People were anxious to figure out what was happening next during this time."

The anxiety is suitable. The size of the big data presents storage issues which is solvable with hardware and cloud computing. However, mining and analyzing this complex data is overwhelming. Thousands of governmental entities and business industries need data miners to analyze big data for their economic forecasting. Companies like TrendPointers capture massive amounts of data from assorted mainstream media sources.

They then code this data into meaningful information for clients. One of the main problems that businesses face is defining a clear objective of what to do with the data. Spitzer advises, "With big data, it's all about identifying what's coming up, as it is coming up..." Obviously, attaining massive amounts of data doesn't help a company's leadership solve all problems. However, when clear organizational directives are in place, the data can help them to make wiser decisions in the face of upcoming trends.

Still, with the continual evolution of the web big data will continue to amass and demand new strategies to handle its complexity. This is especially the case considering the public's concern with personal privacy. As more data is interweaved and connected into business markets, it will undoubtedly affect society to a greater measure. For instance, data mining is responsible for its closely related activity -- predictive analytics.

According to TrendPointers, predictive analytics is still very vague and several entities do not know how to gain benefits from this tool. Since the data is extremely volatile, constantly flowing, and increasing in size conventional method of capturing and analyzing is ineffective. However, specialized data applications using predictive analytics can effectively gauge economic sensitivity in an unlimited number of fields. Data miners similar to TrendPointers are using new data measurement applications that offer accurate and early indicators of insightful information. Businesses can thus get a snapshot of closely and loosely related fields that affect their operations.