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MediumData EngineeringTheorydbt & Transformation Data Modeling

Data Quality — Diagnosing Three Trust-Eroding Incidents

You are a data engineer at a company where the analytics team has lost trust in the data warehouse after three incidents:

(A) A revenue dashboard showed incorrect numbers for three weeks before anyone noticed.

(B) A table silently stopped updating after an upstream API changed its authentication method.

For each incident:

Identify which dimension of data quality (completeness, accuracy, consistency, timeliness, uniqueness, validity) was violated.
Describe what monitoring would have caught it earlier — specifically what you would alert on, what threshold you would use, and where the alert would route.
Describe what you would implement to prevent recurrence — be concrete: dbt tests, observability tooling, schema contracts.

Conclude with a one-paragraph rebuilding-trust plan you would propose to the analytics team.

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