Which of these metrics is NOT typically associated with schema on the fly?

Schema on the fly is a feature associated with data handling in which the schema is defined dynamically as data is ingested, rather than being rigidly established beforehand. This approach allows for greater flexibility and rapid integration of diverse data sources.

Cost savings are often realized because organizations can avoid the extensive upfront work and resources typically required to define schemas before data ingestion. This flexibility contributes directly to time to value since businesses can quickly start extracting insights from their data without being held back by lengthy preparation phases. Furthermore, operational simplification results from the reduced complexity in managing fixed schemas, allowing teams to work more efficiently with varying data formats.

However, data completeness does not specifically tie to the schema on the fly approach. While schema on the fly enhances the ability to ingest various data types and formats, it does not inherently guarantee that all necessary data is captured in a complete manner. Completeness is more affected by the processes implemented around data collection and ingestion rather than the methodology of how schemas are applied. Therefore, data completeness stands out as a metric not typically associated with schema on the fly.