Get Rid of Your Data Quality Problems
summary
HEDDA.IO ships a management app plus notebook runners that push business rules into customer compute (Databricks/Fabric) and keeps everything in the Azure tenant; a demo project scores 55% quality after 217 executions. It defines knowledge bases/domains, applies member lists and ~15 match algorithms including Levenshtein distance, auto-corrects values (F → female) while retaining originals, exposes per-run scores, supports events (Teams/WhatsApp), Excel add-in and versioned publishing.
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chapters (6)
- 0:00Data quality challenges
- 15:43Data quality dimensions
- 21:43Demo: HeiO validation
- 37:45Data quality in pipelines
- 47:23HeiO new features
- 49:53Q&A
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