Scaling Statistics: Incremental Standard Deviation in SQL with dbt

Incremental aggregation in SQL helps maintain efficiency when recalculating metrics for large datasets. This is particularly useful for complex calculations like standard deviation, which involves updating both the mean and the sum of squared differences. By using algebraic manipulation, a formula for incremental computation can be derived, avoiding the need to recalculate from scratch with each new data point. The example provided demonstrates how to implement this using dbt, enabling efficient and scalable real-time data aggregation.