# Check a table-wide measure Shape / inspect A variant of [Check data quality](https://meridian.online/operations/check-data-quality). Compute one measure over the whole table, such as the row count, share of nulls, mean or age of the newest row, and check it against a threshold. Page: ## Status Runs as a SQL step. arcform carries it as a `sql:` step today. ## The DuckDB step check row count, null share, mean and age of the newest row against thresholds It reads the `orders` table the proofs share. Create it first: ```sql CREATE TABLE orders AS SELECT * FROM (VALUES (1, 'Alice Ng', 'north', DATE '2026-01-03', 120.00, 'widget', 'a|b', '{"channel":"web","items":[1,2]}'), (2, 'alice ng', 'north', DATE '2026-01-05', 80.50, 'gadget', 'b', '{"channel":"shop","items":[3]}'), (3, 'Bob Okafor', 'south', DATE '2026-01-05', 300.00, 'widget', 'a|c', '{"channel":"web","items":[4,5,6]}'), (4, 'Carla Díaz', 'east', DATE '2026-01-09', NULL, 'gizmo', NULL, '{"channel":"web","items":[]}'), (5, 'Bob Okafor', 'south', DATE '2026-01-12', 45.25, 'gadget', 'c', '{"channel":"phone","items":[7]}'), (6, 'Dev Patel', 'west', DATE '2026-01-12', 510.00, 'widget', 'a', '{"channel":"web","items":[8,9]}'), (7, 'Carla Diaz', 'east', DATE '2026-01-20', 99.99, 'gizmo', 'b|c', '{"channel":"shop","items":[10]}'), (8, 'Dev Patel', 'west', DATE '2026-02-02', 510.00, 'widget', 'a', '{"channel":"web","items":[8,9]}'), (9, 'Eve Larsen', NULL, DATE '2026-02-03', 15.00, 'gadget', NULL, '{"channel":"web","items":[11]}'), (10, 'Alice Ng', 'north', DATE '2026-02-10', 220.00, 'gizmo', 'a|b|c', '{"channel":"phone","items":[12,13]}') ) t(order_id, customer, region, order_date, amount, product, tags, meta); ``` Then run the statement: ```sql -- the check is made as of a fixed date, so it gives the same answer on every day it is run CREATE TEMP TABLE metrics AS WITH m AS ( SELECT count(*) AS row_count, 1 - count(amount) / count(*) AS null_share, avg(amount) AS mean_amount, DATE '2026-02-15' - max(order_date) AS newest_age_days FROM orders) SELECT 'at least 10 rows' AS rule, row_count AS measured, row_count >= 10 AS passed FROM m UNION ALL SELECT 'no more than 20% of amounts missing', null_share, null_share <= 0.2 FROM m UNION ALL SELECT 'mean amount between 200 and 210', mean_amount, mean_amount BETWEEN 200 AND 210 FROM m UNION ALL SELECT 'newest order at most 7 days old', newest_age_days, newest_age_days <= 7 FROM m; -- the same check as a gate: HAVING keeps the row only when the measure meets the threshold CREATE TEMP TABLE gate_passes AS SELECT count(*) AS row_count FROM orders HAVING count(*) >= 10; CREATE TEMP TABLE gate_fails AS SELECT count(*) AS row_count FROM orders HAVING count(*) >= 11; SELECT rule, round(measured::DOUBLE, 4) AS measured, passed FROM metrics ORDER BY rule; SELECT CASE WHEN ((SELECT map_from_entries(list((rule, passed) ORDER BY rule)) FROM metrics) = MAP {'at least 10 rows': true, 'mean amount between 200 and 210': false, 'newest order at most 7 days old': true, 'no more than 20% of amounts missing': true} AND (SELECT measured::DOUBLE FROM metrics WHERE rule LIKE 'newest%') = 5 AND (SELECT round(measured::DOUBLE, 4) FROM metrics WHERE rule LIKE 'mean%') = 211.1933 AND (SELECT round(measured::DOUBLE, 2) FROM metrics WHERE rule LIKE 'no more%') = 0.1 AND (SELECT count(*) FROM gate_passes) = 1 AND (SELECT count(*) FROM gate_fails) = 0) THEN 'as expected' ELSE error('the four table-wide measures should be 10 rows, 0.1 null share, a mean of 211.1933 (outside 200 to 210) and a newest row 5 days old, and HAVING should pass at 10 and fail at 11') END AS verdict; ``` It needs nothing installed beyond DuckDB itself. ## What other tools call it Meridian's classification; an independent blind rating agreed on 95.7% of 324 rows (variant, version 3). - dbt-utils: [`at_least_one`](https://raw.githubusercontent.com/dbt-labs/dbt-utils/main/README.md) (read 2026-09-27) - dbt-utils: [`not_constant`](https://raw.githubusercontent.com/dbt-labs/dbt-utils/main/README.md) (read 2026-09-27) - dbt-utils: [`not_null_proportion`](https://raw.githubusercontent.com/dbt-labs/dbt-utils/main/README.md) (read 2026-09-27) - dbt-utils: [`recency`](https://raw.githubusercontent.com/dbt-labs/dbt-utils/main/README.md) (read 2026-09-27) - Duckle: [`Freshness Check (SLA Gate)`](https://github.com/slothflowlabs/duckle/blob/f85f8960edfb6efbf4cb89d58a7b32e16df0e867/frontend/src/workflow-ui/palette-data.ts) (read 2026-09-25) - Duckle: [`Run Baseline`](https://github.com/slothflowlabs/duckle/blob/f85f8960edfb6efbf4cb89d58a7b32e16df0e867/frontend/src/workflow-ui/palette-data.ts) (read 2026-09-25) - AWS Glue: [`Completeness`](https://docs.aws.amazon.com/glue/latest/dg/dqdl-rule-types.html) (read 2026-09-27) - AWS Glue: [`DataFreshness`](https://docs.aws.amazon.com/glue/latest/dg/dqdl-rule-types.html) (read 2026-09-27) - AWS Glue: [`DistinctValuesCount`](https://docs.aws.amazon.com/glue/latest/dg/dqdl-rule-types.html) (read 2026-09-27) - AWS Glue: [`Mean`](https://docs.aws.amazon.com/glue/latest/dg/dqdl-rule-types.html) (read 2026-09-27) - AWS Glue: [`RowCount`](https://docs.aws.amazon.com/glue/latest/dg/dqdl-rule-types.html) (read 2026-09-27) - AWS Glue: [`StandardDeviation`](https://docs.aws.amazon.com/glue/latest/dg/dqdl-rule-types.html) (read 2026-09-27) - AWS Glue: [`Sum`](https://docs.aws.amazon.com/glue/latest/dg/dqdl-rule-types.html) (read 2026-09-27) - AWS Glue: [`UniqueValueRatio`](https://docs.aws.amazon.com/glue/latest/dg/dqdl-rule-types.html) (read 2026-09-27) - AWS Glue: [`Uniqueness`](https://docs.aws.amazon.com/glue/latest/dg/dqdl-rule-types.html) (read 2026-09-27) - Apache Hop: [`Evaluate rows number in a table`](https://hop.apache.org/manual/latest/workflow/actions/evaluatetablecontent.html) (read 2026-09-27) - SQLMesh: [`at_least_one`](https://github.com/SQLMesh/sqlmesh/blob/23b237cea7218cc8f338b89c14f0957394a0003b/docs/concepts/audits.md) (read 2026-09-27) - SQLMesh: [`chi_square`](https://github.com/SQLMesh/sqlmesh/blob/23b237cea7218cc8f338b89c14f0957394a0003b/docs/concepts/audits.md) (read 2026-09-27) - SQLMesh: [`kl_divergence`](https://github.com/SQLMesh/sqlmesh/blob/23b237cea7218cc8f338b89c14f0957394a0003b/docs/concepts/audits.md) (read 2026-09-27) - SQLMesh: [`mean_in_range`](https://github.com/SQLMesh/sqlmesh/blob/23b237cea7218cc8f338b89c14f0957394a0003b/docs/concepts/audits.md) (read 2026-09-27) - SQLMesh: [`not_constant`](https://github.com/SQLMesh/sqlmesh/blob/23b237cea7218cc8f338b89c14f0957394a0003b/docs/concepts/audits.md) (read 2026-09-27) - SQLMesh: [`not_null_proportion`](https://github.com/SQLMesh/sqlmesh/blob/23b237cea7218cc8f338b89c14f0957394a0003b/docs/concepts/audits.md) (read 2026-09-27) - SQLMesh: [`number_of_rows`](https://github.com/SQLMesh/sqlmesh/blob/23b237cea7218cc8f338b89c14f0957394a0003b/docs/concepts/audits.md) (read 2026-09-27) - SQLMesh: [`stddev_in_range`](https://github.com/SQLMesh/sqlmesh/blob/23b237cea7218cc8f338b89c14f0957394a0003b/docs/concepts/audits.md) (read 2026-09-27)