Data Quality & Lineage Monitor · Documentation

User Journey

The end-to-end path through Data Quality & Lineage Monitor, from trigger to outcome.

Data Quality & Lineage Monitor
  1. 1

    Check → finding

    Each rule runs daily over its entity and produces a score: pass if the score clears the threshold, warn if it is just under, fail if it is well under. Scores are trended over 14 days. The degrading rule (media-asset count per property) crosses from pass into warn and fail as the window advances, populating the alert path and the seeded audit entry.

  2. 2

    Finding → root cause across the spine

    Click Explain and the metered step hypothesises a cause — usually a concentration of failures in recently-ingested rows, i.e. an upstream pipeline change — and recommends a backfill plus a freshness guard. The lineage graph makes that traceable: it shows #01 Marketplace writing booking and payment, events rolling up into #24 KPIs and #23 BI, and cost flowing into #27 FinOps. Data quality is the layer that tells the rest of the ecosystem whether those reads can be trusted.

User Journey · Data Quality & Lineage Monitor · Abhishek Saxena