A data engineer is setting up a new Databricks pipeline that ingests clickstream events from...

Databricks describes the Bronze layer in the Medallion Architecture as the raw ingestion layer , where source data is landed with minimal validation or transformation so that the original records are preserved for auditability and reprocessing. This is especially important for sources like Kafka clickstream events and file-based product catalogs, because downstream logic such as cleansing, deduplication, conformance, and business modeling should happen later in Silver and Gold layers. Bronze data is commonly stored in an append-only pattern and may include basic ingestion metadata, but it should not be heavily transformed at this stage. Databricks explicitly recommends limiting cleanup and validation in Bronze and using Silver for validation and deduplication. That makes option C the best match to Databricks guidance. Options A, B, and D all skip or misuse the Bronze layer, which reduces traceability and makes recovery or replay harder if business logic changes later.

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