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Module
Module 4 of 6Lesson 1 of 2~16 min

QA and monitor data collection

One wrong number on a dashboard can steer an entire roadmap before anyone notices. This lesson shows a PM how to check an event before release, monitor collection afterward, and investigate an anomaly before reading it as a change in behavior. These habits prevent decisions made on top of a bug.

Take this lesson: your first course is freeSee the full syllabus

Lesson objective

By the end of this lesson, you will be able to QA an event before release, set up simple collection monitoring (volumes, ratios, reconciliation with the database) and diagnose a data anomaly before drawing a product conclusion from it.

Questions this lesson answers

  • How do you QA an analytics event before shipping it to production?
  • How do you monitor data collection quality after a release?
  • What should you check first when a metric suddenly jumps or drops?

Topics covered

  • data quality
  • tracking QA
  • volume monitoring
  • schema validation

Where it fits

Reliable, compliant data

How do I know my numbers are right, and that I collect them by the rules?

Lessons in this module

  1. QA and monitor data collection (this lesson)
  2. Collect by the rules, consent, CNIL and minimization

What you will learn in this module

This lesson is part of the course Instrument a product and use data to make decisions

  • QA and monitor event collection to get reliable data, and know what to do when it is not.
  • Collect usage data in line with the GDPR and the CNIL rules (consent, audience measurement exemption, minimization, retention period).

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