Big Data is ubiquitous, and marketers are excited about its potential for more specific, accurate targeting. Consumers, however, are becoming increasingly concerned about the online security of their personal information, which has recently proven to be lacking, to say the least.

Storage providers, cloud and otherwise, are stuck in the middle, scrambling to meet the ever-increasing need for larger databases, while providing the level of security being demanded by a world where privacy is disappearing by the terabyte.

A simple look at the amount of data available online is staggering: 2.7 zettabytes of data exist in the digital universe today, and that amount is expected to grow to 35 zettabytes by 2020. Google alone processes 20,000 terabytes every day, an amount that grows daily.


“Sorry, Mr. Burns, but I don’t go in for these backdoor shenanigans. Sure, I’m flattered. Maybe even a little curious. But the answer is no!”

Homer turned down a bribe from his boss, Mr. Burns, after being elected the head of his employees’ union. Granted he thought Mr. Burns was coming on to him, but he gets credit for standing fast in the face of corruption nonetheless. This level of trust is vital for anyone leading a successful team.

There’s a lot of data out there. But what should companies do with it? Not surprisingly, only a small portion of that data is actually being analyzed. Today, companies are analyzing a mere 12 percent of data available to them, suggesting a significant missed opportunity in understanding consumers.

But that’s about to change. Analytics is one of the fastest-growing job fields in the U.S., as more and more companies recognize the need for individuals whose sole job it is to gather and make sense of the available data.

Data Analysts deal with a conundrum: they’re analyzing results from the past to predict the future. As such, the field has a need for individuals who can understand complex models, while also possessing the creative ability to predict future developments. Excellent communication skills are also required, as results and predictions have to be communicated effectively to coworkers who don’t possess the same technical backgrounds in computer science or math.

Bridging this gap between the technical analysis of data and the actions taken to effectively utilize it is the Predictive Analytics Scientist. Contact TS2 to see if your background and experience would make you a good fit for this exciting and growing career!