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    CONNECTIONS / Databricks / Databricks to Google OCI

    Your Databricks lakehouse, wired to Google Ads offline conversion import.

    Signals reads the Delta table through a Unity Catalog grant and reconciles closed-won revenue to the Google Ads click through GCLID, hashed on the way out and governed like any other lakehouse job.

    Talk to our team Explore the setup

    databricks -> google-oci :: live

    1. ● databricks → google.oci :: live
    2. > read main.sales.pos_ledger rows=37,739
    3. hash sha256(email,phone) consent=filtered
    4. route google deliver
    5. ✓ delivered · 33,588 matched

    WHAT THIS ENABLES

    Databricks to Google Offline Conversions

    Databricks to Google Offline Conversions: A notebook job reads the offline and in-store sales in your Databricks Delta tables, and Signals reconciles closed-won revenue to the Google Ads click through GCLID, hashed and consent-checked each time the model rebuilds.

    • Signals reconciles closed-won revenue to the Google Ads click through GCLID, reading your Databricks Delta tables each time the model rebuilds.
    • Smart Bidding trained on booked revenue instead of a mid-funnel proxy, fed by data engineers modeling in Databricks notebooks.
    WHAT FLOWS WHERE

    The click, the conversion, and the credit.

    The conversion happens off Google, away from any pixel. Here is how Databricks closes the loop.

    Google credits the campaign that sourced the conversion conversion happens off-platform Ad click on Google D Delta table sync recorded in Databricks S Signals hash · dedupe Offline Conversion Impo… delivered · credited
    WHO THIS IS FOR

    Built for the teams that own the number.

    Advertisers whose Google-sourced deals close days after the click, with the numbers already modeled in Databricks Delta tables governed by Unity Catalog.

    Data engineers modeling in Databricks notebooks who need Smart Bidding trained on booked revenue instead of a mid-funnel proxy.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A Unity Catalog-scoped service principal on the single Delta table in play to feed Google Ads' Offline Conversion Import (Google Ads API), sized for GCLID coverage.

    2. Map

      A notebook job reads your Databricks Delta tables, and its columns map to Google Ads' Offline Conversion Import (Google Ads API) in the visual mapper, hashed and checked for GCLID coverage.

    3. Deliver

      Each time the model rebuilds, Signals reconciles closed-won revenue to the Google Ads click through GCLID, reads only the rows the model rebuilt, with GCLID coverage watched in the debugger.

    WHAT YOU GET

    What changes when the CSV goes away.

    Capability Manual CSV upload Datahash
    Reporting Offline sales sit in a separate export, reconciled by hand. Revenue counted in the same OCI reporting as web conversions.
    Deduplication A re-uploaded file risks counting the same conversion twice. Deduped delivery, so a resent record never counts as a second conversion.
    Match visibility Match quality is a guess until the numbers look off. Match rate reported per upload, tied to the source event set that produced it.
    Effort and latency An analyst exports and uploads on a manual cadence. Server-side and automatic the moment Databricks records the event.
    ON THE WIRE

    What OCI actually receives.

    signals :: databricks.google-oci :: wire

    1. ● signals :: event payload
    2. > POST /offline_conversion_import source=databricks.main.sales.pos_ledger
    3. gclid "Cj0KCQjw…" · conversion_action "closed_won"
    4. conversion_date_time "2026-07-17T01:31:27"
    5. conversion_value 38585 · currency_code SAR
    6. ✓ accepted · batch=daily
    RELATED USE CASES

    Adjacent moves on the same stack.

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    Google Offline Conversion Import

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    FAQ

    Asked on almost every call.

    How often does the Databricks Google OCI sync run?

    Cadence follows the job that rebuilds the table: a nightly model gives Google Ads a nightly feed, an hourly one an hourly feed. Because a run picks up only the rows the model rebuilt, Smart Bidding trained on booked revenue instead of a mid-funnel proxy keeps pace on GCLID coverage and job-cluster time stays modest.

    What match rate should a Databricks-sourced Google OCI batch expect?

    Identifier quality in the Delta table drives it, not the cluster size. Rows carrying a live hashed email or phone land; rows with neither will not, and no rebuild changes that. The opening run's feedback from Google Ads' Offline Conversion Import (Google Ads API) flags the gap for advertisers whose Google-sourced deals close days after the click tracking GCLID coverage.

    NEXT STEP

    Databricks to Google OCI, in production this week.

    Talk to our team All Databricks use cases