Three 'revenue' numbers in three dashboards
Symptoms
- Each team aggregated bronze differently
- No gold owner
Interactive Databricks interview questions on Medallion Architecture. Same topic as /learn/databricks/medallion. Bronze keeps the raw files. Silver is typed and joined. Gold is the metric table BI actually queries.
Question 1 of 3
What are bronze, silver, and gold for?
Answer it out loud, then reveal. Play steps through like the simulators.
Case 1 of 1 · symptoms
Symptoms
Indexed as FAQ. Open any item if you prefer a list to Play.
What are bronze, silver, and gold for?
Medallion Architecture · tap to open the answer
Short: Bronze = raw replay. Silver = conformed truth. Gold = product metrics.
Detailed: Bronze keeps original bytes. Silver types, dedupes, joins. Gold is the grain BI/ML consume. Arrows only flow downstream.
Common mistake: Medallion as three folders with the same messy table copied three times.
Follow-up: Who is allowed to write back into bronze?
Why not serve bronze to a dashboard?
Medallion Architecture · tap to open the answer
Short: Every filter becomes a full scan of landing JSON, and metrics disagree.
Detailed: Bronze has no stable schema contract. Gold is small, named, and owned. Silver is what jobs share so gold doesn't re-parse.
Common mistake: Skipping silver 'to move faster'.
Follow-up: Where do quality expectations live?
How do you handle a late-arriving correction in medallion?
Medallion Architecture · tap to open the answer
Short: Land it in bronze, merge into silver on the business key, rebuild gold from silver — never patch gold by hand.
Detailed: If you edit gold, you can't reconstruct yesterday. MERGE in silver with event time. Gold is a projection.
Senior: Drop silver+gold, rebuild from bronze, numbers match. If they don't, gold had hidden logic.
Common mistake: UPDATE gold.daily_revenue in a notebook because finance asked.
Follow-up: What's the replay test?