Data Engineering & Analytics

A source backfill can change historical counts after reports were published, leaving teams unsure which totals are correct. Checks to make Record the backfill scope and time, compare affected partitions before and after, rerun quality and reconciliation checks, and identify reports that need restatement. Communicate changes to owners and preserve the...

A dashboard can load successfully while its underlying model or semantic layer no longer reflects current business definitions. Checks to make Check model build time and version, source freshness, metric definitions, and recent schema changes. Compare a known sample with an authoritative source, then update lineage and notify report owners if results...

A volume drop may reflect tracking changes, ingestion delay, filtering, consent behavior, or a real change in activity. Checks to make Compare source counts, ingestion lag, schema and filter changes, and event volume by platform and route. Use an independent business signal to distinguish collection failure from demand change, and annotate any affected...

Replayed events can inflate metrics when consumers do not distinguish retries from new business actions. Checks to make Use stable event IDs and idempotent processing, document replay windows, and monitor duplicate rates by source. Test reprocessing from checkpoints and ensure corrections flow through downstream aggregates. When to get help Data...

Local time transitions can create repeated or missing clock hours that affect daily grouping and comparisons. Checks to make Define reporting timezone, store event timestamps consistently, and test the transition date with known records. Document how repeated or missing local hours are handled and compare totals with UTC-based aggregation. When to get...

A correction can update past totals and create confusion when reports do not show refresh timing or revision history. Checks to make Trace the correction through source, transformation, and aggregate layers; identify affected dates and metrics; and document the reason for revision. Preserve prior published outputs where required and notify report...

A pipeline can continue to publish after a validation failure if checks only log warnings or run after downstream refresh. Checks to make Define blocking quality rules for critical datasets, order checks before publication, and mark failed outputs as unavailable or provisional. Alert data owners and test that a deliberate failure stops dashboard...

A new exchange-rate feed can alter historical values, conversion timing, or treatment of missing rates. Checks to make Record source and rate effective time, compare representative currencies and reporting periods, and reconcile totals with approved finance references. Document backfill policy and clearly label any restated metrics. When to get help...