Need for Data Scientists Defeats the Big Data Purpose

Michael Vizard

One of the biggest problems with Big Data is the whole notion that organizations need to hire data scientists in order to be able to work with it. In case you have not noticed, there are not that many data scientists actually walking around these days.

That’s what makes version 7.1 of Alteryx Strategic Analytics worth noting. According to Alteryx President George Mathew, if only a handful of people can really take advantage of Big Data, it more or less defeats the purpose of making the investment in the first place.

Version 7.1 of Alteryx provides 17 new pre-packaged R tools for functions like Decision Trees, Lift Charts and Plot of Means. In addition, version 7.1 provides packaged data from Tom Tom, Experian Marketing Services, Dun & Bradstreet and the 2010 U.S. Census, as well as firmographics from the world's leading business data supplier in every license.

Also included are native connectors for MongoDB, along with more robust Hadoop integration for Cloudera and MapR Technologies' distributions of Hadoop.

Outside of Wall Street and Fortune 500 organizations, most companies can’t afford to have a data scientist. They are lucky to have anybody who could be called a data analyst. It’s really going to be up to the providers of analytics applications to find ways of making all that data more accessible. Once that happens, notes Mathew, it will make sense for the average organization to start investing in collecting all that Big Data.

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