Data Bridge is where you move customer data in and out of UMAP360 — import a spreadsheet of customer traits, or export your profiles as a CSV file. You build each flow as a pipeline, run it when you need it, and watch its results from one screen.

What you can do today

Right now Data Bridge supports two things:

  • CSV import — upload a spreadsheet of customer traits and map its columns to profile fields.
  • CSV export — download your profiles as a CSV file.

You'll see other sources (like Shopify, WooCommerce, and Razorpay) and other destinations (like Google Sheets, BigQuery, HubSpot, and ad-platform audiences) listed in the pipeline builder, but they're marked Coming soon and can't be selected yet.

A few terms

A pipeline is one configured flow from a source to a destination. A source is where data comes from (a CSV upload), a destination is where it goes (a downloadable CSV), and a run is a single execution of that pipeline.

Create a pipeline

  1. Open Data Bridge from the sidebar.
  2. Click New Pipeline to open the 3-step wizard.
  3. Work through the steps:
StepWhat you do
1. SourceChoose where the data comes from. Only CSV Upload is selectable today.
2. ConfigureGive the pipeline a clear name (e.g. "Customer Traits Import"). For a CSV source, drop in your file and map each column to a profile field — email, phone, user ID, or a trait.
3. DestinationChoose where the data goes. Only CSV Export is selectable today.
  1. Click Create Pipeline.

Check your column mapping

Any CSV column you don't map is ignored. Double-check the mapping before you create the pipeline so nothing important gets dropped.

Run a pipeline

Pipelines don't run on a background schedule — they run when you trigger them. There are two cases:

  • Import — your CSV file is processed at the moment you create the pipeline.
  • Export — click the Run / Export (▶) action on a pipeline row to generate a fresh CSV of your profiles.

The schedule shown on a CSV pipeline reads as manual for this reason.

Monitor your pipelines

The Data Bridge dashboard lists every pipeline, with a row of summary cards across the top:

CardWhat it shows
Records — Latest RunRecords processed in each pipeline's most recent run, added up across all pipelines
Active PipelinesPipelines that are currently enabled (paused ones aren't counted)
Import SourcesPipelines pulling customer data into UMAP360
Export PipelinesPipelines pushing profiles out to external tools

Pipeline status at a glance

Each pipeline row shows a status pill:

StatusMeaning
RunningThe pipeline is executing right now
SuccessThe last run finished without errors
ErrorThe last run hit a problem (the message appears under the pipeline name)
StaleA run has been stuck for over 10 minutes, so you can spot a stalled run
InactiveThe pipeline is paused or disabled
Never runThe pipeline was created but hasn't run yet

See the details of a run

Click the Run history (clock) icon on a pipeline row to open its run-history drawer. Each run shows its start time, status, records processed, duration, the error message for failed runs, and what triggered it.

When a run fails

  1. Read the error message for the failed run — it shows up under the pipeline name and on each row in the run-history drawer.
  2. Common causes include:
    • Schema mismatches — your source data changed shape, so revisit the column mapping.
    • Data validation failures — the source data doesn't meet what the destination expects.
    • Connection or rate-limit issues — the destination is unreachable or throttling.
  3. Fix the issue, then click the Run / Export (▶) action on the pipeline row to try again.

A few good habits

  • Use descriptive names so your whole team understands each pipeline at a glance.
  • Test with a small file first before importing or exporting a large dataset.
  • Set up alerts so you're notified when a pipeline fails — see Alerts.

Next steps

Last updated 2026-06-11

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