Numbers you'd stake your quarter on.
Every column scored on five dimensions. When a number moves, trace it to the row, the test, and the timestamp.
Data Quality
A traffic light you can read in a meeting.
Three colours. Green, yellow, red.
Good
Trust it.
Warning
Drill in. Something's off.
Critical
Don't publish until it's fixed.
How the score is computed
Five dimensions, rolled up into one number.
- Completeness. Cells with a value.
- Uniqueness. Primary keys with no duplicates.
- Validity. Test-suite pass rate.
- Freshness. Latest row vs. expected cadence.
- Referential Integrity. Foreign keys that resolve.
Every column. Every test. One screen.
Expand any source to see the failing column and test.
Data Quality
Column-level quality assessment across your data sources.
Every red light comes with a way to fix it.
Detecting is the easy half. Pillar gives the same person three ways to fix it without a ticket.
Upload a spreadsheet
Upload a CSV. Merge on the primary key. No engineer needed.
Connect a database
Link a side database. We join the missing columns into staging.
Override the mapping
Pick which source wins. One dropdown.
Scoring runs wherever your data lives.
Scoring runs on every supported warehouse.
Integrated SQL Data Lake 
Tests that write themselves.
You map a connector. We generate the tests. Not-null on every key, uniqueness on every PK, sanity bounds on every timestamp, join audits on every FK. No YAML.
Fresh or it doesn't count.
Other quality tools score what's in the warehouse. We also score when it got there. Stale beats missing.
Each table has a freshness SLA. Exceed it and the source flips to Warning or Critical.