Adaeze Okonkwo

Maintenance and staff turnover, not launch, determine whether custom editing tools stay trustworthy.

Database-level row security lets teams skip custom tools for scoped editing.

Role-based access patterns let non-engineers query live data without database credentials.

Self-serve analytics require governance first to prevent metric disagreement as teams scale.

AI systems fail on real databases because they lack business context, not reasoning power.

Let support teams safely edit live data without exposing sensitive customer records.

Centralize access logs across databases, BI tools, and platforms to meet compliance demands.

Governing your data layer first makes self-serve analytics work, not better interfaces.

A schema migration can break metrics silently, producing wrong numbers that look plausible.

dbt versioning prevents dashboard breakage when data models change, but only inside dbt itself.

Shared definitions eliminate conflicting metrics and the trust problems that come with them.