For decades, data scientists (née statisticians) have had sandboxes to explore data and find valuable insights. In what seemed like a happy compromise, analysts could quickly load, manipulate, and combine enterprise and industry data in search of new insights and predictions without worry that they would compromise sensitive data or production workflows. While this accelerated creating new insights, putting them into production was a nightmare. A bevy of custom code and data created in an ungoverned environment needed to be converted, quality controlled, and optimized before deployment. It often took the better part of a year for a business to get value from an insight gleaned in a few weeks.
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May 02, 2017 at 04:58AM
from Paul Barth
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