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Ale Cabrera
Ale Cabrera
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SHIPPED · ZAPIER · 2 WEEKS

Self-Serving Monitoring Data Tool

A no-code monitoring test builder on top of the open-source Great Expectations library, moving the team from reactive firefighting to proactive data quality.

2 weeks, POC to shipped

  1. Day 1
    Kickoff: evaluate Great Expectations, scope the POC
  2. Week 1
    Validate: internal cross-user testing against the existing stack
  3. Week 2
    Ship v1: self-serve monitoring live inside the Data Catalog UI

How a test is added

  1. + New monitoring test
  2. Table, schema, alert channel
  3. Passing, or alert sent

Two risks, and what happened

RiskHow it was handledResult
Usability. An in-house monitoring solution existed, but required coding skills few data team members or stakeholders had.A self-serve layer attached to the existing Data Catalog app. "Great Expectations" confused users, so the feature was renamed "monitoring test".Any team member adds tests and routes alerts to their own channels, no backlog ticket needed.
Value. Tables and dashboards were breaking silently. Missing data reached production reports before anyone noticed.Evaluated the open-source Great Expectations library rather than build from scratch. A build-vs-buy call made in weeks, not months.Fewer last-minute failure discoveries, more lead time to fix issues before they hit downstream reports.

My role. Made the build-vs-buy call to adopt an existing OSS library rather than extend the in-house coded solution, and drove the naming simplification after user testing.

With engineering. Integrated directly into the Data Catalog app's existing UI and backend rather than standing up a separate tool, a deliberate choice to reduce surface area, made with the engineers who owned that app.

Product leader with a data scientist past · Zapier, Clearbit, HubSpot

Product doc: ale-cabrera.com/portfolio/self-serve-monitoring