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Delta Lake: foundations first

A data platform is judged on the day a flow fails. Bronze, silver, gold, and what each layer promises.

Published on · 1 min readdata, Databricks, Delta Lake

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A data platform is not judged on demo day but on the day a flow fails at three in the morning. That is when the foundations count.

Three layers, three promises

  • Bronze: the data as it arrived, timestamped, never modified. Everything can always be recomputed from it.
  • Silver: the data cleaned, typed and de-duplicated, with its quality rules written down and checked on every load.
  • Gold: the data ready for one use, modelled for a dashboard or an application, and nothing else.

Why Delta Lake

The Delta format brings what plain Parquet files lacked: transactions (a load succeeds completely or not at all), version history (read the table as it was yesterday) and MERGE for incremental updates.

Make every flow replayable

A flow must be rerunnable for a given date without duplicating data. In practice: idempotent loads, explicit date windows in Data Factory, and a MERGE on a business key instead of a blind append.

Quality, written as code

The rules ("an amount is never negative", "every order has a customer") live in the repository next to the notebooks, and block promotion to silver when they fail. Wrong data in gold costs far more than a delay.

Speed comes after

Streaming, real-time dashboards, machine learning: all of it stands only if the layers underneath are reliable. I always start there.

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