This page is the Google Cloud overview. The BigQuery answer and its TestGen walkthrough cover service account setup and query cost in detail.
What Google Cloud gives you natively
Dataplex Universal Catalog became Knowledge Catalog on April 10, 2026. Its auto data quality runs rules on BigQuery and Iceberg REST Catalog tables. Each rule maps to one of seven dimensions, from freshness to uniqueness, and data profiling can recommend rules for you. It’s serverless and already in your console.
The limits, per Google’s overview checked in October 2026: up to 1,000 rules per scan, and column-level scores only through the API. Anomaly scanning isn’t part of auto data quality at all. Google points you to the separate data profile scan for that.
Tools worth considering on Google Cloud
| Tool | Profiling | Generated data tests | Observability monitors | Data quality dashboards | Runs in-platform | Open source | Price basis |
|---|---|---|---|---|---|---|---|
| DataOps TestGen | 55 column characteristics | 34 test types | Freshness, volume, schema, custom metrics | Scorecards per table group | SQL jobs inside BigQuery | Apache 2.0 | Free for one connection; $100 per user and $100 per connection per month |
| Knowledge Catalog (Dataplex) | Data profile scans | Rule recommendations from profiling | Anomalies via data profile scan | Data quality scores | Serverless in Google Cloud | No | Data compute units |
| Monte Carlo | Yes | Partial | ML-based; BigQuery freshness, volume, schema | Yes | SaaS | No | Credits; pricing on request |
| Soda | Yes | Partial | Metric monitoring and anomaly detection | Yes | Self-hosted runner option | Soda Core, Elastic License 2.0 | Free plan; Team $750 per month |
Sources, checked October 2026: Monte Carlo integrations, which list BigQuery with field-level lineage; Soda data sources, which list GCP BigQuery and Google CloudSQL; and Soda pricing. “Partial” ratings come from DataKitchen’s Monte Carlo and Soda comparisons, reviewed June 2026.
Cloud Storage files
TestGen doesn’t read GCS. Its file connections, added in TestGen 5.134.0, cover a local path, Amazon S3, and Azure Blob Storage. If your vendor drops land in a GCS bucket, test them after they load into BigQuery, or copy them to a location TestGen reads. Better to learn that here than on day two.
Who should pick what
Pick Knowledge Catalog if your governance team already lives in it and wants rules next to the catalog. Pick Monte Carlo if you want a managed service with ML anomaly detection and BigQuery lineage, and the budget fits: DataKitchen’s comparison estimates $120,000 to $250,000 a year for 10 users and 1,000 tables.
Pick TestGen if you want the tests written for you. It added BigQuery in October 2025, profiles every column, and generates tests from the profile, all as query jobs in your project. The core profiling, testing, and monitoring engine is free and open source. Enterprise adds team access, security, Commercial Pharma tests, source-data controls for AI, and support.
See also: which databases TestGen supports and install TestGen.
Documentation: Connect your Data, Access Requirements, Manage Connections, Monitor Tables. DataKitchen’s docs have no BigQuery quickstart as of October 2026.