Forecasting with Limited Data - a Practical Approach

The focus is on the theoretical construct of time-series data mining with a special emphasis on dimension reduction and similarity analysis in support of time-series clustering. It also coalesces the data mining techniques and panel series analyses by presenting an application designed to formulate introductory distributions and life-cycle curves for new or retiring products, markets, and services.

Learn how to incorporate a structured judgmental approach for

• analyzing time series
• generating forecasts in support of practical applications.

Who should attend: Professional forecasters and business analysts who need to forecast products or services with little history or products and services that are near the end of their life cycles

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