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

So far, we used one standard deviation from the mean or a z-score of ±1 to identify anomalies. Changing the z-score threshold can affect our results. For example, let's see what anomalies we identify when the z-score is greater than 0.5 and when it is greater than 3:

Learn how to optimize the Z-score in a way that anomaly detection becomes easier. 

Optimizing Z-score

Learn how to optimize the Z-score in a way that anomaly detection becomes easier.

Detecting Anomalies

Analyzing A Server Log

Backtesting

Improving Accuracy

Optimizing Z-score