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Explain Bronze/Silver/Gold Layers.

Spark/Big Dataeasy0.4 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Altimetrik
Expert AnswerPremium
71 wordsInterview-ready
**Why medallion matters**: Layered design enables incremental processing, schema evolution, and clear ownership. **Bronze**: Raw ingested data; append-only; schema-on-read; minimal transform. Preserves lineage. **Silver**: Cleaned, validated, deduplicated; schema enforced; merged/SCD. **Gold**: Business-level aggregates; optimized for consumption (BI, ML). **Scalability trade-offs**: Bronze = storage growth; Silver/Gold = incremental....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Altimetrik. The answer also includes follow-up discussion points that interviewers commonly explore.

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