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Web sites and transactional databases collect large quantities of time-stamped data. Businesses often want to make future predictions based on numerous sets of time-stamped data (sets of transactions). The number of time series to forecast, however, may be enormous or the forecasts may need to be updated frequently, making human interaction impractical.
This detailed white paper proposes a technique for automating large-scale forecasting using SAS Forecast Server. You will learn about time series data, forecast modeling and statistics of fit. The paper also provides a step-by-step explanation of the automated forecasting technique and a brief discussion of implementation.
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