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

What is the mean of the following series?

1, 2, 3, 4, 10

What is the mean of the following series?
1, 2, 3, 4, 10

What is the standard deviation of the following series?

1, 2, 3, 4, 10

What is the standard deviation of the following series?
1, 2, 3, 4, 10

What would be the z-score of the value 6.5 in series with an average of 3 and standard deviation of 3.5?

What would be the z-score of the value 6.5 in series with an average of 3 and standard deviation of 3.5?

What would be the z-score of the value 10 in series with an average of 3 and standard deviation of 3.5?


What would be the z-score of the value 10 in series with an average of 3 and standard deviation of 3.5?

If we consider any values with a z-score greater than 1 an anomaly, which of these values will be considered an anomaly?

1, 2, 3, 4, 10

If we consider any values with a z-score greater than 1 an anomaly, which of these values will be considered an anomaly?
1, 2, 3, 4, 10

If we consider any values with a z-score greater than 3 an anomaly, which of these values will be considered an anomaly?

1, 2, 3, 4, 10

If we consider any values with a z-score greater than 3 an anomaly, which of these values will be considered an anomaly?
1, 2, 3, 4, 10

Quiz 1