Sorry ARIMA, but I'm Going Bayesian Stitch Fix Technology – Multithreaded

When people think of "data science" they probably think of algorithms that scan large datasets to predict a customer's next move or interpret unstructured text. But what about models that utilize small, time-stamped datasets to forecast dry metrics such as demand and sales? Yes, I'm talking about good old time series analysis, an ancient discipline that hasn't received the cool "data science" rebranding enjoyed by many other areas of analytics. Yet, analysis of time series data presents some of the most difficult analytical challenges: you typically have the least amount of data to work with, while needing to inform some of the most important decisions. For example, time series analysis is frequently used to do demand forecasting for corporate planning, which requires an understanding of seasonality and trend, as well as quantifying the impact of known business drivers.