With business analytics, the toughest challenge is collecting data needed for questions one needs answered. My emphasis here is on:
– must-have answers, not – desired answers!
This is the third post in a series of entries about big data. Others so far are:
New technqiues will not do
Often, we focus on predicting or forecasting the future. However, in management it is more important to understand the analytic HOWs and WHYs. These matter more than the promise of prediction. In the past we did not call things predictive analytics but forecasts instead. We used
– time series, as economists still often do, and – tried our luck with multivariate analysis (both part of what is called parametric statistics). These days, we still use the above methods. However, new ones have come to the fore, such as:
– k-means clusters, and – random graphs.