Data quality you can prove.
Bad numbers come from bad data you never saw. Sluice checks every source as it lands, quarantines what fails with a reason, and keeps every downstream KPI traceable to the rows that survived.
Quality checks at ingestion, not after
Most tools discover data problems in the dashboard — too late. Sluice runs quality checks in the Bronze layer as data lands: null and type violations, duplicate and key checks, and value-shape drift. Rows that fail are quarantined into a reason table, so you can see exactly what was dropped and why — not silently discarded.
Drift you can watch
Data quality isn't one-time. Sluice tracks per-column baselines (median/MAD, distinct counts, top values) and flags drift over time, so a source that quietly changes shape raises a signal instead of corrupting your KPIs.
Quality that flows into trust
Because checks run before the governed Silver layer, every answer the AI analyst gives is built on data that passed them — and stays provable to source. Quality isn't a report you read; it's a property of every number you get.
Frequently asked
- When does Sluice check data quality?
- As data lands in the Bronze layer — before it reaches the governed model — so problems are caught at the source, not discovered later in a dashboard.
- What happens to rows that fail a check?
- They're quarantined into a reason table that records what failed and why, so nothing is silently dropped and you can review every exclusion.
- Does it detect data drift over time?
- Yes. Sluice tracks per-column baselines and flags drift, so a source that changes shape raises a signal instead of quietly corrupting your KPIs.
Catch bad data before it becomes a bad number.
Connect a source and see the quality checks and quarantine reasons in minutes.