When it comes to ingesting data into a warehouse, incremental ingestion often appears to be intuitively superior. It is cost-effective, updates changes to existing records, and inserts new ones.
So, why do we even need a full refresh?
The Two Silent Killers of Data Quality
1. Data Drift
Hard Deletes: When a hard delete occurs at the source, it won’t be reflected at the target, resulting in “ghost records.”
Logic Evolution: Changes in logic, such as a tax reduction from 14% to 12%, necessitate updates to existing records to ensure accuracy in historical reports or refunds.
2. Schema Evolution
New columns may be added to the source with non-null values for pre-existing rows. An incremental run often cannot backfill these new values into the history already stored in your warehouse.
The Bottom Line
While incremental ingestion is beneficial for performance, full refreshes are essential for maintaining data integrity. An effective strategy is to balance performance and accuracy by leveraging frequent incremental syncs complemented by a recurring full-refresh cycle.
The pattern I recommend: run incremental syncs frequently (hourly or daily), and schedule a full refresh on a weekly or bi-weekly cadence depending on your data’s volatility. This way you get the performance benefits of incremental loads while periodically correcting any drift that accumulated between full refreshes.