Gain insights into using SQL for anomaly detection. Delve into applying mean, standard deviation, and z-score to identify and investigate data anomalies, enhancing your analytical skills.

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Learn how to identify anomalies in your data using SQL. Understand how to apply mathematical concepts such as mean, standard deviation, and z-score to detect when an anomaly occurred in your data and how to investigate past data to improve and refine the model.

Simple Anomaly Detection using SQL

In the process so far, we’ve used several constants in your calculations:

- Lookback period: How far back we calculate the mean and standard deviation for each status code. The value we used is 60 minutes.
- Entries Threshold: The least amount of entries we want to get an alert for. The value we used is 10.
- Z-Score Threshold: The z-score after which we classify the value as an anomaly. The value we used is 6.


Learn how using different values impacts the outcome of the calculations.

Detecting Anomalies

Analyzing A Server Log

Backtesting

Improving Accuracy

Experiment with Different Values