DATA OPS
Governed BigQuery extract to Dropbox with PII masking and Slack approval
Fulfills an ad-hoc data export request by running a BigQuery query, masking PII columns, then waiting for a Slack approval before delivering the file to Dropbox.
How it runs
The automated pipeline, trigger to output.
- TriggerExport request submitted via form webhookHTTP webhook
- ActionRun parameterized query in BigQueryBigQuery
- LogicMask columns tagged as PII
- LogicPost summary to Slack and wait for approvalSlack
- ActionWrite masked CSV to requester's Dropbox folderDropbox
- OutputSend Slack confirmation with Dropbox linkSlack
What it does
Turns a one-off "can you pull this data for me" request into a controlled pipeline. It runs the requested BigQuery query, automatically masks columns flagged as PII (email, phone, SSN), and holds the result behind a Slack approval button so a data owner signs off before the file ever leaves the warehouse. Only after approval does the masked CSV land in a shared Dropbox folder.
When to use it
Use it when analysts or business teams request data exports that may contain customer PII and your governance policy requires a human approval before delivery. It replaces the risky pattern of running a query and emailing a raw CSV.
How it works
- 1A form submission (webhook) captures the requested dataset, query, and requester.
- 2BigQuery runs the parameterized query and returns the result set.
- 3A masking step redacts any column tagged as PII, leaving safe columns intact.
- 4An approval branch posts the row count and column list to Slack and pauses for an approve/reject decision.
- 5On approval, the masked CSV is written to the requester's Dropbox folder.
- 6A Slack message confirms delivery with the file link; rejection ends the run.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect DropboxFiles and folders.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Connect HTTP webhookTrigger any URL on agent actions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
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