GOLD namespace
The GOLD namespace for the Lakehouse provides a simplified, curated layer for human users and AI tools. It contains pre-joined tables that make it easier to navigate and analyze data in the Lakehouse.
The GOLD namespace is built natively into the Lakehouse catalog. Tables are kept in sync with the underlying metadata in real time -- no setup, refresh schedules, or customer-managed compute required.
Design
The GOLD namespace follows a star schema design. The ASSETS table is the central hub that contains every asset in the catalog along with common attributes like name, type, status, owners, and certification. The surrounding detail tables (RELATIONAL_ASSET_DETAILS, GLOSSARY_DETAILS, BI_ASSET_DETAILS, etc.) contain domain-specific columns for particular asset categories.
All detail tables share guid as their primary key, so joins to ASSETS are always a simple assets.guid = [detail_table].guid. Start every query from ASSETS, filter to the assets you need, then join to the relevant detail table for specialized columns.
Structure
The GOLD namespace consists of the following tables:
ASSETS
Core lookup table that lists all assets and important attributes. Primary entry point for all queries.
RELATIONAL_ASSET_DETAILS
Details about relational assets, including databases, schemas, tables, views, and functions.
GLOSSARY_DETAILS
Details about glossaries, categories, and terms in Atlan.
DATA_QUALITY_DETAILS
Details about data quality checks from Anomalo, Soda, and Monte Carlo.
PIPELINE_DETAILS
Details about data pipelines and ETL processes.
BI_ASSET_DETAILS
BI-specific attributes for PowerBI, Tableau, Looker, and Sigma assets.
DATA_MESH_DETAILS
Details about data mesh assets in Atlan, including data products and domains.
Tags, custom metadata, readmes, and lineage data aren't in the Gold namespace. Query entity_metadata directly:
| Use case | Table |
|---|---|
| Tags applied to assets | entity_metadata."tagrelationship" |
| Custom metadata values | entity_metadata."custommetadatarelationship" |
| Asset readmes | entity_metadata."readme" |
| Lineage processes | entity_metadata."process", entity_metadata."columnprocess" |
Common query patterns
These examples use Snowflake-compatible SQL.
Data products
List all data products:
SELECT asset_name, asset_qualified_name, status
FROM gold.assets
WHERE asset_type = 'DataProduct'
AND status = 'ACTIVE';
To include data mesh details (criticality, sensitivity, ports), join with gold.data_mesh_details:
SELECT
a.asset_name,
dm.data_product_status,
a.asset_qualified_name,
dm.criticality,
dm.sensitivity,
dm.visibility,
dm.input_port_guids,
dm.output_port_guids,
dm.data_domain
FROM gold.assets a
JOIN gold.data_mesh_details dm ON a.guid = dm.guid
WHERE a.asset_type = 'DataProduct'
AND a.status = 'ACTIVE';