Google BigQuery

Query and model data in BigQuery. Writes performant GoogleSQL, partitions and clusters tables to cut scan costs, builds scheduled queries and materialized views, and manages datasets, UDFs, and BI Engine for fast, cheap analytics.

This skill works with Google BigQuery: writing performant GoogleSQL, partitioning and clustering tables to minimize bytes scanned and cost, building scheduled queries, materialized views, and authorized views, using UDFs and window functions, tuning slot usage and BI Engine, and modeling analytics tables for downstream dbt and BI tools.

When to use

Use when writing or optimizing BigQuery SQL, partitioning and clustering tables to cut cost, building scheduled queries or materialized views, or modeling analytics data in BigQuery.

Examples

Cut a costly query

Partition pruning

This BigQuery query scans the whole events table. Rewrite it to prune partitions and cluster so it scans far fewer bytes

Design a table

Partition + cluster

Design a partitioned and clustered BigQuery table for web events optimized for date-range and user-id filtering

Scheduled rollup

Automate a daily job

Write a BigQuery scheduled query that appends a daily active-users rollup into a summary table