# Freshness Detailed article on freshness can be found here. Data is timely when it is up-to-date (current), and available on time. Freshness is the delay after which data is considered as complete. Timeliness can be associated with various levels including metadata. Is the metadata available and up to date at the time someone is attempting to use it to understand the data he or she is accessing? ![](/files/5gXlRWYhoDEjUTCKLfo1) ## Measuring Freshness Measure of time between when data is expected versus made available The degree to which data represent reality from the required point in time The length of time between data availability and time of the event or phenomenon they describe The extent to which the age of the data is appropriate for the task at hand The degree to which data is available when knowledge workers or processes require it A measure of how current a data item is The degree to which the period between the time of creation of the real value and the time that the dataset is available is appropriate **Unit of Measure**: Time difference **Related dimension:** Accuracy because it inevitably decays with time**.** --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.telm.ai/academy/data-quality-indicators/freshness.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.