Learn to identify and address irregularities in data using SQL. This module covers detecting anomalies, backtesting techniques, and server log analysis to improve your database's efficiency.

Become a Database Professional with SQL

In this module, we’ll focus on detecting anomalies in data using SQL. We’ll explore how to apply mathematical concepts like mean, standard deviation, and z-scores to identify anomalies. Additionally, we’ll delve into backtesting techniques to investigate past data and refine our detection models. We’ll also cover server log analysis to improve and optimize the overall efficiency and scalability of databases.

Anomaly Detection

Another way to represent a range of acceptable values is using a z-score. Z-score, sometimes called standard score, is the number of standard deviations from the mean. In the previous section, our acceptable range was one standard deviation from the mean, or in other words, a z-score in the range ±1:

Understand the intuition behind the Z-score.

Understanding Z-score