Characterizing the Workload


Regardless of how amazing a forecast model may be, without quality workload data and an appropriate characterization of the workload, it’s totally worthless. That’s a pretty strong statement, but it’s the truth. Both projects and products fail when the workload is not properly characterized. When raw workload data is transformed into useful information, a model’s precision capabilities flourish and the usability of the forecasting system is amazing. A solid and appropriate characterization of the workload is probably the most critical aspect of forecasting.


Glean Drone Subsys 


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Copyright information

© Craig Shallahamer 2007

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