GlossaryEN1 min readUpdated: Jul 18, 2026
Data Quality
Data quality describes how complete, accurate, up to date, and consistent the data is on which logistics and customs processes are built.
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Source: https://en.wikipedia.org/wiki/Data_quality
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Passar Hub: Everything on the new Swiss customs system
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Definition & Explanation
Data quality describes how complete, accurate, up to date, and consistent the data is on which logistics and customs processes are built. In freight forwarding and customs it directly determines the reliability of operations: an incorrect commodity code in the master data blocks the customs declaration, an outdated delivery address misroutes a shipment, inconsistent weight figures distort freight calculation. Key quality dimensions are completeness, accuracy, consistency, timeliness, and uniqueness. The more companies rely on automation, transport management systems, and AI-supported dispatching, the more critical high data quality becomes—because faulty input data propagates unchecked through system integration. It is safeguarded by validation rules, duplicate checks, maintenance processes, and overarching data governance. For shippers and customs declarants, data quality is therefore not a marginal IT topic but an operational prerequisite. Not to be confused with data quantity—the mere volume of available data, which creates no value without quality.
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⚡ Current 2026
Passar Hub: Everything on the new Swiss customs system
Passar replaces E-dec and NCTS. Passar 1.0 (export) is live, Passar 2.0 (import) starts from Q2 2026. Roadmap, ePortal registration, deadlines and FAQ — all on one page.
Passar 1.0Passar 2.0 → Q2 2026Passar 3.0 → Q2 2027
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