Find and export
your Databricks data.

1. 1List the tables in the catalogs and schemas in scope with the required access.
2. 2Run DESCRIBE DETAIL catalog.schema.table for each relevant Delta table.
3. 3Record sizeInBytes, numFiles and the table identity, then convert the non-overlapping sizes to GB.
4. 4Inspect business timestamps for the history represented by the rows.

Report in GB, naming catalogs, schemas and the current-snapshot basis. Add table and row quantities where available.

Describe retained historical states and external files separately, with the earliest business dates and application scope.

1. 1Have an administrator confirm the table types, privileges and approved destination.
2. 2For supported Delta tables, review DEEP CLONE to create an independent copy of the required data and metadata.
3. 3Use a supported query export or data-writing route where another format or table type is required.
4. 4Collect the output with schemas and table identifiers, checking historical-state requirements separately.

A clone of a selected state does not preserve every earlier table version or all catalog metadata.

Managed-table storage should be accessed through authorized Databricks operations. Use a supported export destination rather than bypassing table permissions.

Lakehouse tables can link raw events with the structured records derived from them.

Schema and pipeline context can explain how business activity becomes a usable dataset.

Choose catalogs, tables and fields in scope, reviewing sensitive data and any externally shared material.

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.