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Monday, April 25, 2011

UCL=LCL : How many standard deviations do we use for Control Charting? Use ZERO!

How many standard deviations do we use for upper (UCL) and lower (LCL) limits calculations on a control charts? 3? 1? What about 0 st. dev.!? Indeed, the simplest way to build MASF data for exception detection is to use 168 weekly hours averages as a baseline, so that would be the case when ZERO st. Dev is used to make UCL=LCL! Plus for further simplification the current data could be included in wider historical baseline (Why not?). My EV meta-metric in this case would be just difference between actual metric value and the average over baseline!

Here is example of DB2-like SQL script to implement that approach. It is based on real script I developed and successfully tested against real data for BIRT tool to get exceptional servers list:

(In this SQL script example metrics names as well as some other fields parsing (e.g. week day and hour) are dropped to increase readability; for real usage that script needs to be adjusted to the real PDB type, metrics names and schema.)

So the SEDS-lite project could be implemented using BIRT reporting (no real programming needed – just SQL scripting and report design!) and the script above could be a good example of ETL step on the SEDS-lite architecture for building SEDS DB out of raw data (see my other post linked here) for charting and exception detecting

"Все гениальное - просто" = KEEP IT SIMPLE!  

GACMG presentation about Statistical Pattern Recognition Techniques

Tim Browning, one of my guest blogger (check his post here) and the author of interesting book "Capacity Planning for Computer Systems" will be presenting the following paper on this spring Greater Atlanta CMG meeting:

Statistical Pattern Recognition Techniques for Performance Analysts and Capacity Planners.