Google’s chief economist thinks the world needs more data scientists

Not that long ago, the concept of “Big Data” was pretty abstract. Few companies considered it feasible to sift through huge sets of data looking for speculative insights. The hurdles to collecting and analyzing information at scale were large, tied to the cost of setting up a data warehouse and buying expensive analysis software. 

Also, data to supplement company-owned information was expensive and hard to come by. Not anymore. Cloud computing from companies like Amazon and Microsoft eliminate the need for a data warehouse. Powerful, and free, data analysis programs like R and Python make number crunching cheap. Tons of free datasets are available from governments and companies like Google and Kaggle. Easy-to-use machine learning algorithms are freely available from TensorFlow and Caffe.

Author: Dan Kopf

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