Publishing a dataset for other teams or consumers to use

Publishing datasets in BigQuery means making them discoverable and consumable by other users, teams, or the wider organization while controlling who can access them and how they can query them. This typically involves using IAM permissions, authorized views/datasets, Analytics Hub for sharing, and clear documentation of schema and usage.

1 · Learn the must-know

• 1BigQuery datasets can be shared using IAM roles (e.g., bigquery.dataViewer, bigquery.user) at the dataset, table, or project level to control read/query access.
• 2Authorized views and authorized datasets let you share query results or curated tables without granting direct access to the underlying source data, enabling row/column-level abstraction.
• 3Analytics Hub is the Google Cloud service purpose-built for publishing and subscribing to datasets (as 'listings' within 'exchanges') both within an organization and externally, including commercial data sharing.
• 4Publishing a dataset via Analytics Hub creates a linked dataset for subscribers that stays in sync with the publisher's source data without duplicating storage or copying data.
• 5Labels, descriptions, and BigQuery's data catalog (via Dataplex/Data Catalog integration) help make published datasets discoverable and well-documented for consumers.
• 6Cross-project and cross-organization sharing requires careful IAM setup (including VPC Service Controls considerations) to avoid unintended data exposure while still enabling collaboration.

2 · Check your understanding