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Define the decision and the record
Start with the decision the report should support. Then state what one row represents: an order, an order line or a payment. Mixing these levels can inflate totals after a join. Record the source, key fields, date meaning, currency and expected update frequency before building charts.
Agree the rules that matter
Specify completeness, uniqueness, validity, consistency and freshness checks for the fields that affect the decision. For example, an order identifier may need to be unique, a quantity may need to be positive and the most recent extract may need to arrive before a daily review. Set thresholds with the business owner; there is no single acceptable threshold for every dataset.
Prevent what you can; detect the rest
Database constraints can enforce rules such as required values, uniqueness and relationships between tables. PostgreSQL documents CHECK, NOT NULL, UNIQUE and foreign-key constraints. These controls do not establish that a real-world fact is accurate: a valid-looking customer address can still be wrong. Combine structural validation with reconciliation and source-level investigation.
Give exceptions an owner
Do not silently delete records just to make a report look clean. Separate rejected or questionable records, preserve enough context to investigate and identify who can resolve the issue. Record the correction and decide whether to reprocess affected outputs. Where the issue is material, explain the limitation to report users.
Make trust visible
Show the reporting period, last refresh, metric definitions and any unresolved limitation beside the dashboard. Reconcile key totals against the source before release. A small quality register with a rule, result, owner and next action is often a more useful first step than a complicated monitoring platform.
