Using the SQLExecutor for Data Quality Management: aka One man’s love for the SQLExecutor

The SQLExecutor is one of FME’s most powerful and flexible transformers. Pivvot maintains a robust internal metadata hierarchy used to support ingestion and curation of thousands of external data sources that must be managed for quality before entering our platform. By using the SQLExecutor, Pivvot can efficiently detect problems and perform analysis before data is extracted from our staging environment, removing the need for rollbacks or cycles waisted on a failed job. This presentation will walk through three distinct examples of how Pivvot uses the SQLExecutor to engage its metadata hierarchy and integrate with its Data Quality Management workflows efficiently and within the source postgres database. Spatial Validation –Validating spatial prerequisites before entering a production environment. Reference Data Validation – Dynamically validate domain-ed columns across any table and multiple columns per table. Practical De-duplication – Removing identical or near-identical well point locations from two distinct source datasets in the same table.