Hey dev community!
I just published the final piece in my data strategy series, and it addresses perhaps the most frustrating problem in data engineering: users who don't trust the data we build for them.
After witnessing countless incidents where a lack of trust derailed data initiatives, I developed a framework built around five key
principles:
- Transparent Data Lineage
- Proactive Quality Assurance
- Incident Response Protocol
- Trust Through Governance
- Culture of Constructive Questioning
The article includes specific implementation techniques, including:
Data validation at ingestion with contract testing
A traffic light system for communicating data health
Model confidence scoring
The Morning Confidence Dashboard pattern
If you've ever built a data pipeline or dashboard only to hear "I don't trust these numbers," this might offer some practical solutions.
Full article: https://cookingdata.substack.com/p/building-culture-data-trust-five-pillars
