What’s Hot & What’s Not in Data Science 2015

Interesting infographics from CrowdFlower. In the hot category, I would add data plumbing, sensor data to better predict Earthquakes, weather or solar flares, predictive analytics for flu and other health or environmental issues, automating data science and man-made statistical analyses, pricing optimization for medical procedures, customized drugs, car traffic optimization via sensor data, properly trained data scientists involved in decision and replacing business analysts, the death of the data silo.

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Comment by Cari Jaquet on January 6, 2015 at 9:06pm

What's hot: Smart Data Prepster. What's not hot: Data Janitors. All too often, data analysts spend more of their time preparing data: cleaning it, pushing it around (wrangling, blending, etc.), leaving no time for the high value analytics work they need to do. 2015 delivers self-service, adaptive data prep solutions (like Paxata) built from the ground up to help even non-technical analysts aggregate, clean, shape, and organize data - in a single platform that offers a single collection point regardless of where data comes from, drives re-usability of AnswerSets, enforces real-world data governance practices,  and allows for enterprise-wide collaboration every step of the way.

Comment by umamahesh on January 3, 2015 at 4:00am

valuable info

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