Summary:  If you’re still writing code to clean and prep your data you're missing big opportunities for efficiency and consistency with modern data prep platforms.

Two things are true. 

• Data prep still occupies about 80% of our model building time – the least enjoyable part.
• If you’re still writing code…

Summary:  Purpose Built Analytic Modules (PBAMs) such as those for Fraud Detection represent a fourth way to practice data science, a new model for the good use of Citizen Data Scientists, and a new market for AI-first companies.

It appears that data science has exited its age of exploration and entered into its…

Summary:  The role of Analytics Translator was recently identified by McKinsey as the most important new role in analytics, and a key factor in the failure of analytic programs when the role is absent.

The role of Analytics Translator was recently…

Summary:  How about we develop a ML platform that any domain expert can use to build a deep learning model without help from specialist data scientists, in a fraction of the time and cost.  The good news is the folks at the Stanford DAWN project are hard at work on just such a platform and the initial results are extraordinary.

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