“Data Scientists and automation (data products, algorithms, production code, whatever) are complementary functions. Good Data Science supports automation. It quickly adds value by investigating, testing, and quantifying hypotheses about existing data and potential new data. Simply switching on software ignores the reality of working with data, regardless of the claims of that software. Data is full of nuances, errors and unknown relationships that are best discovered and tested by an expert Data Scientist. This takes time and does not scale but it does not have to scale. It is the necessary prudent investment that you make before spending months in product development and automation of the wrong algorithm on the wrong or broken data.” Guerrilla Analytics ( July 21, 2015 )

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