by Angela Guess
Alex Woodie recently wrote in Datanami, “There are many reasons why a given organization may be lagging on big data analytics adoption. The shortage of data scientists is one, and the tightening of budgets is another. But according to analytic experts, one of the biggest obstacles to adopting big data is just knowing what is possible. ‘The biggest obstacle we’re running into is not knowing what’s possible. This is the single biggest problem we’re running into,’ says Praveen Kankariya, the founder and CEO of Impetus Technologies, a developer of streaming big data analytic software and services based in Los Gatos, California.”
Woodie goes on, “There are a host of well-worn big data use cases that play across multiple industries, such as reducing customer churn, delivering personalized recommendations, and detecting fraudulent transactions. But all too often, executives have the mistaken impression that even these established paths are beyond their means. In fact, thanks to the democratization of big data technologies driven by the open source community, the solutions are often within reach.”
Woodie continues, “‘People don’t know that it’s doable and one-tenth the order of magnitude of what they imagine, or one-hundredth,’ says Kankariya, whose company plans to hire 150 data scientists, analysts, and data experts in the U.S. this year. ‘People become resigned to a certain way. They say ‘Let’s not go in that direction, it’s not possible.’ Starting a conversation in these large enterprises about whether this is doable or not doable’ is one of Impetus’ biggest focuses this year. Nitin Mittal, principal in Deloitte Consulting‘s analytic practices, echoes that sentiment, saying about one-third of Deloitte’s clients request a high degree of hand-holding when it comes to beginning their analytics journey.”
photo credit: Flickr/ debaird