{"active":true,"blog_title":"Wondering how to incrementally amass data in your data destination? This is how!","blog_url":"https://community.fabric.microsoft.com/blog/fbc_fabricupdatesblogs/wondering-how-to-incrementally-amass-data-in-your-data-destination-this-is-how/5172281","feature_description":"Customers will be able to configure a backup to store a snapshot of a query's results after every dataflow run, in any of the supported data destinations. Each run writes a new, timestamped file or table into the destination the customer chose, so snapshots accumulate side by side instead of overwriting one another.This gives customers a durable record of what their data looked like at each point in time, which today they can only approximate by building a second dataflow, adding a downstream pipeline, or exporting results by hand. With backups in place, customers can look back at a previous run to understand when and where their data changed, compare a surprising result against the last known good snapshot before escalating it, and satisfy audit or record-keeping requirements that call for evidence of what was produced and when. Because snapshots land in a destination the customer already owns, they can be queried alongside the rest of their data, connected to downstream reports, or shared with colleagues who don't have access to the dataflow itself. Each snapshot is a byproduct of a run the customer is already performing, so the history builds itself with no extra artifacts to maintain and no manual steps to remember.","feature_name":"Dataflows - Backup data results across dataflow refreshes","last_modified":"2026-08-18","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"97d41049-3e9b-f111-b8db-6045bd02b663","release_status":"Planned","release_type":"Public preview"}