In Power Query architecture within Power BI, data transformation queries utilize reference and duplicate mechanisms to manage query dependencies while optimizing storage efficiency. The core theoretical mechanism distinguishes between "references," which establish a logical dependency where changes propagate automatically through the ETL chain without duplicating physical data rows, and "duplicates" (copies), which create isolated query branches allowing independent step modification at the cost of potential maintenance overhead regarding identical logic. This domain belongs to Data Engineering and Extract-Transform-Load (ETL) process management, governed by the principle that referencing intermediate results enables modular pipeline design where shared preprocessing steps are applied once upstream while downstream transformations branch logically without increasing memory footprint for raw data storage.
In Power Query architecture within Power BI, data transformation queries utilize reference and duplicate mechanisms to manage query dependencies while optimizing storage efficiency. The core theoreti…