Data Refresh Vs Update

Data Refresh is the process of completely erasing all existing data in the target data warehouse table(s) and replacing it with the entire, newly extracted data set from the source system. The destination table is truncated, and the full data set is reloaded from the source. It ensures the target perfectly mirrors the source at the time of the load. 

Simplicity: The process is straightforward to implement and manage.

Guaranteed Consistency: Eliminates the risk of discrepancies, as it ensures all records are current and aligned with the source.

Ideal for Smaller Datasets: Best suited for dimension tables or small transactional tables where the cost of a full load is minimal.

Incremental Update often referred to as Update in the context of Refresh vs. Update involves identifying only the changes (new records, modified records, and deleted records) that occurred in the source system since the last load, and applying only those changes to the target data warehouse. Only the difference delta between the current and previous states is extracted, transformed, and loaded. 

High Performance: Significantly reduces processing time and resource consumption.

Minimal Downtime: The data warehouse remains operational, as only specific rows or blocks are being updated.

Near Real-Time Readiness: Essential for supporting low-latency reporting and dashboards that require data freshness.