docs: add column_value_anomalies test documentation

[devin-ai-integration]

Summary

Adds documentation for a new column_value_anomalies test — a row-level anomaly detection test that operates directly on raw column values rather than on aggregate metrics (min, max, average) per time bucket.

This is a docs-first PR ahead of implementation in the dbt-data-reliability package. The new page:

• Explains how the test works (z-score on individual row values against historical baseline)
• Differentiates it from the existing column_anomalies test with a comparison table
• Documents supported configuration parameters (timestamp_column, where_expression, anomaly_sensitivity, anomaly_direction, detection_period, training_period, detection_delay)
• Provides YAML examples for models
• Is added to the "Anomaly Detection Tests" navigation group in docs.json

Updates since last revision

• Removed time_bucket and seasonality from the config block and examples. Since this test operates on raw individual values (no per-bucket aggregation), time bucketing is not applicable. The test uses training_period and detection_period directly to define the historical baseline and evaluation windows.
• Updated all YAML examples to use training_period/detection_period instead of time_bucket.

Screenshots

Mintlify preview: https://elementary-devin-1775975833-column-value-anomalies-docs.mintlify.app/data-tests/anomaly-detection-tests/column-value-anomalies

Note: Screenshots below were captured before the time_bucket removal. Use the Mintlify preview link above for the current rendered page.

Review & Testing Checklist for Human

• Verify the described behavior matches the intended design — the doc states the test computes mean+stddev from training period values and z-scores each row in the detection period. Confirm this is the correct detection approach before the implementation PR lands.
• Confirm time_bucket and seasonality should be excluded — these were intentionally removed since this test doesn't aggregate per bucket. Verify this aligns with the planned implementation.
• Check that timestamp_column should be required — this doc says it's required, unlike other anomaly tests where it's "highly recommended." Confirm this is desired.
• Review which config params are included/excluded — the config block omits ignore_small_changes, anomaly_exclude_metrics, and dimensions that other anomaly tests support. Verify whether these should be supported for this test type.
• Preview the rendered page — use the Mintlify preview link to confirm the table, <Note> block, and <pre> config block render correctly.

Notes

• The corresponding implementation PR for dbt-data-reliability has not been created yet — this PR documents the intended API surface.
• The test is scoped to numeric columns only as stated in the <Note> block.
• Mintlify deployment and link-rot CI checks passed. The two failing checks (code-quality, create_pylon_issue) are pre-existing issues unrelated to this PR.

Link to Devin session: https://app.devin.ai/sessions/97ebe636d57244fb82a7452e1521604e
Requested by: @arbiv

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