Data Class A / B / C (reliability)
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Definition
A three-tier label describing how tightly a data series can be trusted, from a single-source class-A original to a frozen class-C snapshot.
How to read it
The class tag tells you how a number was produced, which is the first thing you should know before trusting it. Class A = a tightly-reconstructable original: it comes from one authoritative source (a government filing, an exchange, a central-bank series) and you could rebuild it yourself from that source. Class B = a wider composite: several inputs blended, modeled, or estimated together — more coverage but more room for methodology error. Class C = a frozen snapshot: a point-in-time capture that is no longer updating, useful as a historical reference but not a live reading. Higher purity (A) means you can trust a single reading on its own; lower purity (B/C) means treat it as directional and cross-check.
How practitioners use it
Used as context among multiple indicators — never as a standalone signal to act.
Less common professional uses
Power user: when a Class B composite and its underlying Class A component diverge, the divergence itself is information about the model's assumptions. Caveat: a Class A series can still be stale — class describes provenance/purity, not freshness. Always check both the class and the 'as of' timestamp. Some panels upgrade a series from B to A once a free sovereign source is wired in; the class legend reflects the current best source, so re-check it over time.
Sources & provenance
Portal data-provenance framework
This page is educational content published by Pachira Aquatica Global LLC. It is not investment advice and not a recommendation.