The Medallion Data Architecture: An Introduction
A CSV arrives from one system, JSON comes from another, a Parquet file from somewhere else. Weeks and months go past, and before you know it, nobody is quite sure which version of the data can be trusted, which rules have been applied to it, or why an error occurred on yesterday’s dashboard. The medallion architecture is a practical response to that problem.
- ▪A CSV arrives from one system, JSON comes from another, a Parquet file from somewhere else.
- ▪Weeks and months go past, and before you know it, nobody is quite sure which version of the data can be trusted, which rules have been applied to it, or why an error occurred on yesterday’s dashboard.
- ▪The medallion architecture is a practical response to that problem.
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| Original publisher | Towards Data Science |
| Canonical URL | https://towardsdatascience.com/the-medallion-data-architecture/ |
| Publication time | Tue, 04 Aug 2026 16:30:00 +0000 |
| Retrieval time | 2026-08-04T16:35:41.368Z |
| Last seen | 2026-08-04T16:35:41.368Z |
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| Commercial reuse | May the content be reused commercially? | Not permitted |
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Opening excerpt (first ~120 words) tap to expand
Data Engineering The Medallion Data Architecture: An Introduction A practical guide to Bronze, Silver and Gold, with a working Python and DuckDB example Thomas Reid Aug 4, 2026 14 min read Share Image by AI Data ETL pipelines tend to become harder to trust as they grow in scope, and they certainly become harder to run without errors, to document, and to debug. A CSV arrives from one system, JSON comes from another, a Parquet file from somewhere else. Weeks and months go past, and before you know it, nobody is quite sure which version of the data can be trusted, which rules have been applied to it, or why an error occurred on yesterday’s dashboard. The medallion architecture is a practical response to that problem.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.
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