Make your Databricks data shine with Golden
Databricks Unity Catalog has certifications, documentation, and metadata your team spent time building. Golden actually uses all of it.
If your company runs on Databricks, there is a good chance your data is in better shape than you think. Unity Catalog has been around long enough that serious data teams have done the work: documenting tables, certifying trusted assets, tagging deprecated columns, and linking to internal runbooks. The catalog is real and useful, and for many companies it has become a valuable source of institutional knowledge.
If you’ve already invested in building out the Gold layer of your medallion architecture, we think it deserves a Golden experience on top.
The surprising part is how little of that metadata makes it into the analytics experience. Most BI tools connect to Databricks, read the schema, and stop there. Descriptions, certification badges, links to documentation — all of that context is left behind. You end up with essentially the same experience you would get connecting to any database.
Golden is built differently. We use the work your data team has already done.
Search your catalog, not just your schema
Enterprise catalogs are too large to navigate by expanding folders and hoping you recognize the right table name. People search.
With Golden, you can search by table names, column names, descriptions, and the business concepts your data team has documented. If someone wrote a description like “subscription revenue recognized per ASC 606 guidelines, excludes trial accounts,” that description becomes part of how Golden understands your business and helps answer questions about revenue.
For most analytics tools, the catalog helps you find tables. For Golden, it helps the AI understand your business.
Documentation should shape the answer
A column called arr_adj might mean five different things. A field called created_ts might be UTC or Pacific, depending on when the table was built. This is exactly why catalog documentation matters.
When your team has invested in writing good descriptions in Unity Catalog, Golden uses that context. Documentation is not just something a human reads after they find the table. It actively helps the AI interpret the data correctly.
Let governance do its job
The governance metadata in Unity Catalog should not just sit there. It should influence the analytics experience.
Golden prioritizes certified tables and trusted assets. Deprecated columns and datasets that your data team has marked for retirement are naturally deprioritized. The result is simple: the governance work your data team does translates directly into better answers for everyone else.
A well-governed Databricks environment and Golden are genuinely complementary.
Live queries. No copies.
Golden does not import your data, maintain extracts, or create another copy that has to be managed. Every analysis runs live against Databricks. Your existing access controls stay in force because the query goes directly to Databricks, and you do not have to recreate your governance model in another system.
The best data teams have already invested enormous effort documenting, governing, and organizing their data. That work should not disappear the moment someone opens a BI tool. It should make every search better, every analysis more accurate, and every answer more trustworthy.
And if you’ve already built a Gold layer for trusted data, it only makes sense to have a Golden experience on top of it.