Calculating Moving Averages in BigQuery

Moving averages are a powerful tool for data analysis, as they allow you to quickly identify trends in data. In BigQuery, you can calculate moving averages using the ARRAY_AGG function. This function takes a set of values and creates an array from them, which can then be used to calculate the moving average.

Examples of using ARRAY_AGG to calculate moving averages in BigQuery

To illustrate how ARRAY_AGG works, let's look at a few examples. In the first example, we'll calculate the moving average of a set of values.

SELECT ARRAY_AGG(1,2,3)

This query will return the following array: [1,2,3]. The moving average of this array is 2.

In the second example, we'll calculate the moving average of a set of values, using a delimiter.

SELECT ARRAY_AGG(1,2,3, DELIMITER=';')

This query will return the following array: [1;2;3]. The moving average of this array is also 2.

Additional info about using ARRAY_AGG to calculate moving averages in BigQuery

ARRAY_AGG is a powerful function that can be used to calculate moving averages in BigQuery. It takes two arguments - the values to be added to the array and an optional delimiter. The delimiter is used to separate the values in the array. The default delimiter is a comma, but it can be any character or string.

It's important to note that ARRAY_AGG is specific to BigQuery. Other databases, such as MySQL and PostgreSQL, have their own functions for calculating moving averages. It's important to check the documentation for the database you're using to make sure you're using the correct syntax.

If you want to learn more about ARRAY_AGG, you can check out the official documentation here.