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- 1. Analyzing Oracle Performance Using Time Series Models <br />Chen (Gwen) Shapirahttp://prodlife.wordpress.com<br />
- 2. Why?<br />Abnormal Data<br />Changes<br />Trends<br />SLAs<br />
- 3. See<br />Techniques<br />Use Cases<br />Real Data<br />
- 4. Techniques<br />
- 5.
- 6. Trend<br />
- 7. Trend<br />
- 8. Moving Average Trend<br />
- 9.
- 10. Remove Trend<br />
- 11. Seasonality<br />
- 12.
- 13.
- 14. Seasonal Effect<br />
- 15. Components<br />
- 16. More AutoCorrelation<br />
- 17. Xt= 0.33Xt-1 + 0.07Xt-2 – 0.09Xt-3+ e<br />
- 18. Test Model<br />
- 19. Use Cases<br />
- 20. Fake Incident<br />
- 21. Detect By<br />Remove trend<br />Remove Seasonality<br />Mark “normal data”<br />What’s left?<br />
- 22. Spot the Incident<br />
- 23. “I have seen the future and it is very much like the present, only longer”<br />KehlogAlbran<br />
- 24. Exponential Smoothing<br />Calculate moving average of future<br />Add seasonality<br />
- 25.
- 26. AutoCorrelation<br /> Use the model:Xt = aXt-1…To calculate Xt+1,Xt+2…<br />
- 27.
- 28. Real Data 1:Redo Blocks per Hour<br />
- 29. Holiday<br />
- 30. Seasonality<br />
- 31. Abnormal Data<br />
- 32. Real Data 2:CPU on DB Server<br />
- 33.
- 34. Seasonality?<br />
- 35. Partial AutoCorrelation<br />
- 36. Check Fit of Model<br />
- 37. Prediction<br />
- 38. Conclusions<br />Use moving average to describe trend<br />Look for seasonality<br />Predict with Exponential Smoothing<br />AutoCorrelation?<br />Seasonality aware monitoring<br />
- 39. Questions?<br />

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It has moving averages, seasonality analysis, linear regression predication, trend analysis, and automated spike analysis, cross database and cross instance analysis, Oracle RAC support, ASH analysis and much more.

Sorry for being too excited, but for me Performance Explorer-i was a treasure chest, and considering my complex, challenging and hugely active production database environment is a life savior.