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[DOCS] Clarify impact of delayed data in anomaly detection (#66816) (#67041)
Co-authored-by: Benjamin Trent <[email protected]>
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docs/reference/ml/anomaly-detection/ml-delayed-data-detection.asciidoc

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[[ml-delayed-data-detection]]
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= Handling delayed data
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Delayed data are documents that are indexed late. That is to say, it is data
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related to a time that the {dfeed} has already processed.
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Delayed data are documents that are indexed late. That is to say, it is data
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related to a time that your {dfeed} has already processed and it is therefore
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never analyzed by your {anomaly-job}.
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When you create a {dfeed}, you can specify a
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{ref}/ml-put-datafeed.html#ml-put-datafeed-request-body[`query_delay`] setting.
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increased delay allows more time for data to be indexed. If you have real-time
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constraints, however, an increased delay might not be desirable. In which case,
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you would have to {ref}/tune-for-indexing-speed.html[tune for better indexing speed].
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