Data Engineering

Snowflake Dynamic Tables and SCD-1: Partial Updates Still Need Thought

Snowflake’s SCD-1 partial update pattern is a reminder that current-state tables are only simple when the source data behaves nicely.

By DataStackSignals Editorial Desk Published 5 min read Source: Snowflake Blog
Snowflake Dynamic Tables and SCD-1: Partial Updates Still Need Thought Abstract data-system illustration for Data Engineering

Key signal

SCD-1 looks simple until the source system starts behaving like a real source system.

What happened

Snowflake published a data-engineering post on managing partial updates with an SCD-1 pipeline, using Dynamic Tables to deduplicate append-only change logs and maintain a clean current-state table. The post also discusses schema evolution and backfill concerns.

Why it matters

Source systems do not always send full records. Sometimes they send only the field that changed. If your SCD-1 logic assumes every event is complete, you can quietly overwrite good values with nulls.

Who it affects

Data engineers building CDC pipelines, Snowflake teams, reporting-layer developers and teams maintaining latest customer, account or transaction state tables.

What data teams should do next

Check whether your change feed is full-row or partial-row. Then design your merge logic around that reality. Review null handling, schema drift, late-arriving updates and backfill behaviour before relying on the table for reporting.

Signal Take

The hard part is not building the table. The hard part is protecting the table from bad assumptions about what the source system will send.

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