Thanks for the excellent article. One more interesting thing I have observed in data projects failing: organizations culture around data and the gap between da

Thanks for the excellent article. One more interesting thing I have observed in data projects failing: organizations culture around data and the gap between data science team and engineers. Say, you have 2 top notch data scientist who know enough (stats, markov chains, algorithms and so on..). But let us say an average engineer in the organization doesn't know even a bit about A/B testing or difference between building a machine learning model Vs. obtaining predictions from already built model. Then no matter how good your so called data scientist are, the end result in terms of product or solution delivery is always sub-optimal. If the engineers and data science teams can't speak a common language, the result is always disastrous. Note that the gap is specifically about understanding data analysis as a domain. The efforts to narrow down this gap must be driven by the lead data science member or CTO. Something like 'data bootcamp' mandatory for every new joinee can help. I had read about Facebook having such a bootcamp mandatory.