In theCUBE’s ongoing coverage of Hadoop Summit 2013, John Furrier and Dave Vellante spoke with CEO and Founder of Tresata, Abhishek Mehta. The three discuss Tresata business strategy, new trends in big data analytics and growing opportunities for emerging businesses with a stake in the “information arms race” among Amazon, Facebook and Google.

Mehta says that one of the biggest industry shifts since founding Tresata is a widespread understanding and appreciation of big data. He notes that in 2011 big data had more skeptics than believers. Now, he argues, there is no question that “big data is here to stay and is a transformative force.”

Given the many ways in which to leverage and optimize big data, Mehta believes that “if we make Hadoop purely a storage platform, we will have failed.” It is important to understand how new shifts in the economy have influenced new trends in consumer behavior and aspirations. Mehta explains that as consumers are recovering from the credit crises, they are engaging in different activities. Companies need insight to understand what these new consumers appreciate. These recent trends can be monetized, but as Mehta puts it, “You can’t monetize a database.”

Omnichannel presence is now the dominant business approach. Although Tresata clients recognize the value in representation across connected devices and social media platforms, Mehta finds customers asking similar recurring questions: “What channels should I be using? How do I collect all the data from these channels? What do I do with it? How do I monetize it?”

Mehta outlines a three-part data pyramid that explains a fundamental flaw in traditional approaches to analytic insight. At the bottom of the pyramid is existing data assets, which addresses the “who” of consumers. The second tier reflects interaction data, which explains the “what” of consumer behavior. The top of the tier is emotions and represents the “why” of what motivates consumers. This apex is often the most important to understand, but the most challenging to determine. The big mistake most companies make with data analytics is that they try to use data from the past to predict future behavior, which will not take into account unforeseen circumstances that might change such behavior. According to Mehta, “You have to be able to look at emotions and interactions [and] attach it to transactions to see what [consumers] do.” He adds that emotions cannot be predicted, but observed through data in the form of hashtags, tweets and “likes.” With search and fast SQL, Mehta says those layers would be quickly commoditized.

As Vellante notes, e-mail and direct mail have limited impact in engaging customers in profitable ways. Mehta explains that companies can use insight to go beyond such traditional approaches in calculated ways. For example, businesses could harness data to decide what is the best social media outlet to present an offer to a certain customer with an understanding of the average percent of expected consumer response. Furrier notes that this new approach is disruptive and might be difficult to explain to an investor. Mehta calls this style of insight, “analytics application” and adds that “very few venture capitalists truly understand what the future of this data analytics looks like.”

When it comes to the big data heavy hitters of Google, Facebook and Amazon, Mehta suggest there’s no question about who has the biggest advantage. He explains that “Facebook knows what you like, Google knows what you search for, Amazon knows what you buy. Guess which one is the most useful?” Vellante adds that with consumer reviews and their own search engine, Amazon actually also knows what you like and search for. Mehta concludes by asserting that a revolution is coming that allows others to compete at the level of the “big guys” using Tresata.