O’Reilly’s Alistair Croll wrote a piece discussing something data scientists everywhere seem to agree with: large companies are not doing enough with their stockpile of data–not by a long shot.

The reason, according to him, is that established organizations have a much harder time “breaking their own business models” than smaller and more agile startups that, in contrast, do in fact put data analytics into good use.

“Early-stage companies have a second advantage over more established ones: they can ask for forgiveness instead of permission. Because they have less to lose, they can make risky bets. In the early days of PayPal, the company could skirt regulations more easily than Visa or Mastercard, because it had far less to fear if it was shut down.”

More traditional businesses are naturally hesitant when it comes to venturing into new areas.  However, startups that are not afraid to explore new terrains have been proven before to have the capacity to trigger industry-wide trends. Companies across multiple sectors are starting to adopt big data analytics, but this movement has a long way ahead.

Revolution Analytics polled some 200 data scientists that attended The Joint Statistical Meeting in Miami and found that 97 percent of the respondents believe big data analytics is not in a position today to answer enterprise needs.  Three key reasons were noted:  the complexity of analytics software, problems applying statistical models to the data and lack of insight.  The last issue is particularly interesting, considering a recent McKinsey study that concluded there will be a shortage of 1.5 million managers who are capable of making data-based decisions in the U.S by 2018.

Companies today are tackling issues with asking the right questions about their data, but the general consensus is that there’s a lot of potential and opportunities out there.  This was also the topic of Sohaib Abbasi’s keynote during the Annual Pacific Crest Technology Leadership Forum. Abbasi is the chairman and CEO of Informatica.