checking-freshness
Verify data freshness by checking table timestamps and update patterns against a staleness scale.
- Identifies timestamp columns using common ETL naming patterns (
_loaded_at,_updated_at,created_at, etc.) and queries their maximum values to determine age - Classifies data into four freshness statuses: Fresh (< 4 hours), Stale (4–24 hours), Very Stale (> 24 hours), or Unknown (no timestamp found)
- Provides SQL templates for checking last update time and row count trends over recent days to spot update gaps
- Integrates with Airflow to diagnose stale data by checking DAG status, run history, and SLA misses; links to the debugging-dags skill for failed pipeline investigation
- Supports both quick yes/no answers and detailed freshness reports with actionable next steps
Data Freshness Check
Quickly determine if data is fresh enough to use.
Freshness Check Process
For each table to check:
1. Find the Timestamp Column
Look for columns that indicate when data was loaded or updated:
_loaded_at,_updated_at,_created_at(common ETL patterns)updated_at,created_at,modified_at(application timestamps)load_date,etl_timestamp,ingestion_timedate,event_date,transaction_date(business dates)
Query INFORMATION_SCHEMA.COLUMNS if you need to see column names.
2. Query Last Update Time
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