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Big Data Analytics predictions for 2014

As we close out the year, we asked a few members of the Revolution Analytics team to make a few predictions about big data analytics, data science and R for 2014. Here's what they came up with (including a few from yours truly). Michele Chambers, Chief Strategy Officer and VP Product Management While the sexiest job in 2013 was the data scientist generalist, in 2014 the focus will shift to data analysts in dedicated business units. The demand for data analysts will rise as data analysts are closer to the business issues, making them the go-to resource for data-based decision making. In 2014, data analysts will be empowered through easy-to-use tool that leverage the insights of data scientists, by providing real-time forecasts and recommendations in their day-to-day business tools. Better analytics will make data analysis more effective, while automation frees up data scientists to focus on strategic initiatives and unlocking further value in corporate data stores. The dam will break for the data scientist supply and demand issue of 2013 for two reasons. First: higher education institutions have quickly adapted to this market need with custom programs to train the next generation of data scientists. In 2014, those grads will be entering the workforce. Second: companies are getting better at carving out focused, big picture projects for data scientists and pushing smaller and line of business projects to business users and data analyst. Greg Todd, Chief Technology Officer 2014 will be the year when predictive analytics with data in Hadoop will become operational. David Smith, VP Marketing and Community  In 2013, the open source programming language R broke through as the go-to statistical software, surpassing SAS. There are nearly three million R users today and this will only continue to grow as students who study and work with R enter the private sector. In 2014, the past 15 years of marketing research combined with Big Data predictive analytics will make one-to-one marketing a reality. Big data analytics help marketers take ideas from general to specific and tailor campaigns directly to the individual level. Consumers understand that data is being collected on them and in 2014 they will come to expect interactions and experiences to be personalized. Marketers have an opportunity to build relationships with consumers or risk losing them due to generic blanket campaigns,” said David Smith, vice president of marketing & community at Revolution Analytics. For more 2014 predictions from Alteryx, Cloudera and Tableau, check out 14 Analytics Predictions for 2014. 

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David Smith is Vice President of Marketing and Community at Revolution Analytics. He has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products.<

David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, he leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, he served as vice president of product management at Zynchros, Inc. Follow him on twitter at @RevoDavid

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