Find and export
your BigQuery data.

1. 1Use the required metadata access in each project.
2. 2Review INFORMATION_SCHEMA.TABLE_STORAGE for each dataset region, or a table's Details → Storage info.
3. 3Record logical bytes and physical bytes separately rather than adding them.
4. 4Inspect row quantities and the earliest relevant business timestamps across the tables in scope.

Report in GB, stating logical or physical storage and the projects, datasets and regions included.

Give table and row quantities where available, the earliest event dates, and whether snapshots or historical retention are included.

1. 1Have the administrator confirm table-export and job permissions plus access to an approved Cloud Storage destination.
2. 2For each table, use Export / sync → Cloud Storage, bq extract or SQL EXPORT DATA.
3. 3Choose Parquet, Avro or another suitable format; use a wildcard destination for output split across files.
4. 4Collect all shards and preserve the schema and table identity.

CSV cannot represent nested and repeated fields in the same way as richer structured formats. Choose the format according to the schema.

Exports can incur processing or storage costs under the selected method. Review table size and applicable quotas before a large collection.

Warehouse tables can connect events across a company's applications and reporting systems.

Dataset descriptions and relationships help explain what an event represents and how it links to later outcomes.

Select projects, datasets and columns in scope, reviewing personal data and unrelated analytical workloads.

Telegraph Lab reviews the proposed material with you and agrees how sensitive information will be handled. Preparation can include excluding material, redacting details and replacing personal identifiers. Your company keeps ownership; the licensing agreement defines the material, permitted uses and authorized recipients.