Source- analyticsinsight.net The promise of machine learning (ML) is vast and investment is increasing, but the results are lagging because too many projects don’t make it to production in an operational system. A Wall Street data scientist recently said to me, “It took us two months to build and train the model and six months to deploy it.” This is the norm. Analytics leaders cite deployment and productionization – aka the “last mile” – as the biggest bottleneck for analytics and ML