1) Perspective (where we are at now)
1) Compiling raw data into useable format – multiple disparate sources / multiple business users / multiple disciplines. Company-owned data (or data from vendor who compiles company-owned data [Nielsen/IRI]) not industry or third party data. Analysis = what happened.
2) Mass data load and analysis through advanced software packages – Python / R / SAS. Data mining. Regression Analysis. Forecasting probabilities and trends. Industry-wide data sets.
3) Application of mathematical and computational sciences. Decision Engineering. Predict what will happen; suggest decisions; display effects/implications of those decisions and explain why all of that did happen or will happen. Additional data includes non-industry specific sets – weather, consumer sentiment, home-buying patterns, etc.