# GoogleCloudPlatform/bigquery-utils

Useful scripts, udfs, views, and other utilities for migration and data warehouse operations in BigQuery.

Repository: https://github.com/GoogleCloudPlatform/bigquery-utils
Canonical: https://ross.abutalabs.com/products/bigquery-utils
Homepage: https://cloud.google.com/bigquery/
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: bigquery, google-cloud-platform, data-warehouse, sql, utilities
Last push: 2026-07-03T02:33:41+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 90, release rhythm 35, longevity 100
- inputs: {"age_days": 2578, "days_push": 62, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1306, forks 335 (observed 2026-08-28T04:04:18.894378+00:00)

## What it is
A Google-maintained collection of utilities for BigQuery, including SQL user-defined functions, stored procedures, views, Python and shell scripts, Looker Studio dashboards, and Colab notebooks. Its focus is on migrating from legacy data warehouses (Oracle, Netezza, Redshift, Snowflake) and on day-to-day data warehouse operations such as billing analysis and query optimization.

## Use cases
- migrate oracle or snowflake sql functions to bigquery
- analyze gcp billing export data in bigquery
- monitor bigquery slot utilization and job errors
- find optimization opportunities in my bigquery warehouse
- compute distinct counts and quantiles with datasketches in bigquery
- build dashboards over bigquery information_schema metadata
- performance test bigquery with jmeter

## When to choose
- You are migrating a data warehouse from Oracle, Netezza, Redshift, or Snowflake to BigQuery and need UDFs that mimic proprietary functions
- You want ready-made dashboards, scripts, and queries for BigQuery cost analysis, slot utilization, and job monitoring
- You need reusable SQL utilities, stored procedures, and automation examples for BigQuery maintained by Google

## When to avoid
- You need a programmatic client SDK to run BigQuery jobs from application code - use the official BigQuery client libraries instead
- You use a data warehouse other than BigQuery, since the utilities are BigQuery-specific
- You need a general-purpose ETL or orchestration platform rather than SQL-centric utilities

## Facets
- artifact type: library
- maturity: active
- function: database, analytics, monitoring, data-science
- domain: databases, big-data, analytics, cloud-computing, developer-tools
- platform: cloud, python, cli
- tags: bigquery, sql, udf, data-warehouse, google-cloud-platform, warehouse-migration, looker-studio-dashboards, datasketches, stored-procedures, cost-optimization, information-schema, data-engineering

## Member repositories
- GoogleCloudPlatform/bigquery-utils (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:18.894378+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:50:56.533998+00:00, confidence not recorded.
  - readme: https://github.com/GoogleCloudPlatform/bigquery-utils (fetched 2026-08-28T04:04:18.894378+00:00, sha 2c9bdda6562e)
  - homepage: https://cloud.google.com/bigquery/ (fetched 2026-08-29T12:08:43.085240+00:00, sha fd3d4f27007c)
- Data as of 2026-08-30T08:39:29.467469+00:00.