Data Science at Scale: from Map-Reduce to Spark
How disruption in Big Data technology is supporting scalability of Machine Learning algorithms to build Predictive Models on massive datasets. The MIT professor Micheal Stonebraker (Turing Award winner in 2014) conducted an extremely interesting seminar at Stanford, on June 2016, about disruption in Big Data technology. I’d like to bring your attention at the presented scenario and to know your feedback, especially if you are passionate in Machine Learning at Scale. Data Science vs BI Data Analytics is essentially two things: BI (Business Intelligence) i.e. simple analytics, based on SQL. It basically provides you with a dashboard of KPIs (Key Performance Indicators) useful to take business decisionsData Science i.e. complex analytics, mainly Machine Learning (regression, clustering, neural network, bayesian analysis, etc.). It gives you a Predictive Model that can be…
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