06.1.4 · Skill in Product instrumentation
Data quality
Making sure analytics data is complete, correct and trusted.
Missing events, duplicates, bots and broken tracking after a release quietly corrupt analysis. Validation, monitoring and tests on tracking catch them. People stop using data they do not trust, so quality is a product feature of the analytics itself.
Resources
2- articleStart hereNaming conventions: why you need them for clean data ↗Twilio Segment · 2026 · 15 min
Explains the object-action naming pattern and shows how messy event names break analysis later.
- docsStart herePlan your taxonomy ↗Amplitude docs · 2026 · 8 min
How to go from business questions to a small set of events and properties, with naming advice.
Tools
1- ToolFreemium