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Database Performance Analytics Using Anomaly Detection
This presentation covers my unique, but strikingly simple, SQL-based approach to anomaly detection among the tens of thousands of Oracle performance metrics which are aggregated on the fly. This is essentially a jet tour through the concepts provided in the book “Dynamic Oracle Performance Analytics Using Normalized Metrics”. Subtopic areas include: why is dynamic metrics analysis needed; comparing traditional analytical methods with the dynamic method; feature engineering; feature selection and related statistical concepts; bundling metrics according to custom taxonomies; building the performance anomaly model and reporting the results. Several case studies are highlighted to show the effectiveness of this novel approach to database performance analysis. This is perhaps at a more advanced level.


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