Definition · data quality
Data freshness
Data freshness is a measure of how recently data was updated relative to the real-world events it represents, and whether it is current enough to rely on for a decision. For data freshness, a useful definition states a measure of how recently data was updated relative to the real-world events it represents, and whether it, who owns it, and which.
Also known as data recency
Why it matters
Understanding data freshness matters because leaders need a shared, source-backed meaning before they can compare results, explain performance, or decide what to do next. Every record Pluvo ingests is timestamped for when it was observed and asserted, so you can see how current each input is and query the books as-of any point in time.
In practice
Operating example
Data freshness is useful when teams need a shared interpretation of a measure of how recently data was updated relative to the real-world events it represents, and whether it is current enough to rely on for a decision. The definition should make source data, timing, ownership, and the decision it supports explicit.
Pluvo example
Every record Pluvo ingests is timestamped for when it was observed and asserted, so you can see how current each input is and query the books as-of any point in time.
In practice, teams should define data freshness with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding data freshness matters because leaders need a shared, source-backed meaning before they can compare results, explain performance, or decide what to do next. Every record Pluvo ingests is timestamped for when it was observed and asserted, so you can see how current each input is and query the books as-of any point in time.
A strong workflow for data freshness separates the definition from the action: first agree what the term means, then decide how it is measured, when it changes, and who is accountable for the next step.
Every record Pluvo ingests is timestamped for when it was observed and asserted, so you can see how current each input is and query the books as-of any point in time.
FAQ
What is data freshness?
Data freshness is a measure of how recently data was updated relative to the real-world events it represents, and whether it is current enough to rely on for a decision. For data freshness, a useful definition states a measure of how recently data was updated relative to the real-world events it represents, and whether it, who owns it, and which.
How is data freshness measured?
Measure data freshness against a defined standard: agreed source data, expected output, review threshold, and owner. That makes the answer testable instead of relying on whether the result merely looks plausible.
Why does data freshness matter in finance?
Understanding data freshness matters because leaders need a shared, source-backed meaning before they can compare results, explain performance, or decide what to do next. Every record Pluvo ingests is timestamped for when it was observed and asserted, so you can see how current each input is and query the books as-of any point in time.