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Add table: ticket_metrics for zendesk support connector

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  • Official comment

    Hi Srinivasa,

    Really appreciate the detail here, especially the specific stuff around author_id = -1 on messaging replies, private opening messages skipping the real first reply, and pausable_update_time.

    I am going to take those three to the team that owns the package and get their read on it. If they're real gaps (and honestly, from your description they sound like they could be), we'd patch them in the package quickly so that you folks get the right metrics downstream.

    Understand your rationale behind ticket_chat_event and other event tables being high MAR, and enabling them just for a few reply metrics does seem counterproductive. That said, we've seen that the majority of customers actually prefer building metrics from raw data, since it also lets them customize to their own workflow, SLAs, etc. The reason we don't sync a pre-computed metrics table directly is that a synced value is locked in at the point it's synced. If a calculation needs correcting later, whether it's a schedule change, an edge case, or something specific to your setup, there's no way to go back and fix it. Building the metrics from the raw ticket, comment, and tag data means it can actually be recalculated correctly when something's off or if you want to customize the calculation as per your logic 

    We're actually looking at a more elegant way to solve this, something that doesn't pile on extra cost on your end while also making sure we're not just syncing a snapshot that could carry the wrong numbers. We'll keep you posted as that takes shape.

    Best,
    Vignesh 
    Fivetran Product team 

    Also, i see there is same feature request with 18 upvotes got rejected. https://support.fivetran.com/hc/en-us/community/posts/1500000704041-Connector-Improvement-Add-table-for-Ticket-Metric-Events-to-Zendesk-Support-connector?page=1#community_comment_43382386269719

    Not sure what is the reason. But, request you to consider this since it is helping not only our team but also others who are using zendesk support connector.

    Hi Vignesh,

    Thanks for looking into those package edge cases with your team.

    The key challenge for us is that we don't actually need custom transformation logic—we rely entirely on Zendesk's native standard definitions, which worked seamlessly in our legacy Meltano/Dataflow pipeline.

    Having to run 61 dbt_zendesk models every hour and sync high-MAR event tables just to populate reply_time_in_minutes and reply_count creates unnecessary compute costs and operational overhead. Ingesting ticket_metrics directly remains the cleanest, most efficient path for our setup. Hope this provides clearer context on why direct ingestion is so critical for us