Question

A retail company runs a mix of workloads in BigQuery. Their nightly ETL jobs consume large, predictable volumes of slots, and their finance team requires stable, predictable monthly billing with no risk of surprise overages. Meanwhile, a small data science team runs occasional ad hoc exploratory queries that are sporadic and low-volume. The data engineering lead must recommend how to organize these workloads to meet the business requirements while minimizing total cost. What should they recommend?

Accepted Answer

Purchase a BigQuery slot commitment (reservation) sized for the predictable ETL workload, and leave the sporadic ad hoc queries on on-demand pricing.

Answer

Put both the nightly ETL and the ad hoc data science queries on on-demand pricing so all teams share a single billing model.

Answer

Purchase a single large slot commitment sized to cover both the ETL and all possible ad hoc query bursts to guarantee no on-demand charges ever occur.

Answer

Move all workloads to on-demand pricing but apply a per-project custom quota to cap monthly bytes billed for the ETL workload.