Ready-to-copy integrations that plug DataScreenIQ into your existing tools. Each integration is a complete, working example you can drop into your project.
| Integration | What it does | Setup time |
|---|---|---|
| GitHub Action | Screen CSV/JSON files on every PR. Block merges when data quality fails. | 2 min |
| Airflow DAG | Quality gate task between extract and load. Stops pipeline on BLOCK. | 5 min |
| dbt post-hook | Screen model output after dbt run. Catch drift in transformed data. |
5 min |
| Prefect flow | Quality gate flow with alerting on BLOCK. | 5 min |
| Google Colab | Interactive notebook — try DataScreenIQ in 60 seconds. | 1 min |
pip install datascreeniq
export DATASCREENIQ_API_KEY=dsiq_live_...Get a free API key (500K rows/month, no credit card): datascreeniq.com
Your source → Extract → DataScreenIQ → PASS ✓ → Load → Warehouse
→ WARN ⚠ → Load + alert
→ BLOCK ✗ → Dead-letter queue
DataScreenIQ is not a replacement for dbt tests or Great Expectations. It fills a different gap: the pre-storage screening layer that catches problems before they propagate.