Three 'revenue' numbers in three dashboards
Symptoms
- Each team aggregated bronze differently
- No gold owner
Interactive Databricks interview questions on Medallion Architecture. Practice with the matching lesson. 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?