Per-source quality scoring implemented

Per-contact quality flags (bounce, invalid email) are only useful if you can trace them back to the source that produced them. Without per-source quality scoring you have no way to quarantine a bad purchased list, deprioritize a scraper hitting stale pages, or negotiate data credits with a vendor whose records are 40% invalid. ISO 25010:2011 §4.2.7 (data quality) requires that data accuracy be measurable and traceable. Absence of source-level aggregation means data rot goes undetected until deliverability collapses.

Add a data_sources table with a quality_score column, then populate it via a periodic aggregation query that computes bounce and invalid-email rates per source.

CREATE TABLE data_sources (
  id            TEXT PRIMARY KEY,
  source_type   TEXT NOT NULL,
  display_name  TEXT,
  quality_score NUMERIC(5,2),   -- 0–100
  last_scored_at TIMESTAMPTZ
);

-- Periodic update (run hourly or daily)
UPDATE data_sources ds
SET quality_score = (
  SELECT 100.0 * COUNT(*) FILTER (WHERE c.email_valid AND NOT c.bounced)
         / NULLIF(COUNT(*), 0)
  FROM contacts c
  WHERE c.source_id = ds.id
    AND c.acquired_at > NOW() - INTERVAL '30 days'
),
last_scored_at = NOW();

• ID: data-sourcing-provenance.source-management.per-source-quality-score

• Severity: medium

• What to look for: Count all quality metrics tracked at the source level. Look for logic that computes or updates a quality score, acceptance rate, or health indicator at the source level — not just per-contact. This might be a source_quality_score on a sources table, a periodic job that calculates bounce rate or invalid-email rate by source, or a dashboard metric grouped by source_id. The key is whether the system can answer "which source is producing the most bad data?"

• Pass criteria: At least 1 mechanism exists to track data quality at the source level: a sources table with a quality metric, a query or aggregation that segments quality by source, or an alerting threshold triggered by per-source bad data rates.

• Fail criteria: Quality is only tracked at the individual contact level with no aggregation back to the source. There is no way to identify which source is producing bad contacts without a manual query.

• Skip (N/A) when: The system has only a single static data source.

• Detail on fail: "No per-source quality tracking found — bounce rates and invalid records are not aggregated by source" or "Quality metrics exist but are global, not segmented by source".

• Remediation: Add a sources table with a quality metric and update it periodically:

  CREATE TABLE data_sources (
    id           TEXT PRIMARY KEY,
    source_type  TEXT NOT NULL,
    display_name TEXT,
    quality_score NUMERIC(5,2),  -- 0-100
    last_scored_at TIMESTAMPTZ
  );
  

  Then run a periodic query to update quality_score based on bounce/invalid rates for contacts from each source.