Design and implement a self-serve analytics layer that enables business users to answer questions without engineering help. Use when improving analyst independence, building a semantic layer, or reducing ad hoc request volume. Triggers: 'self-serve', 'self-service analytics', 'empower analysts', 'ad hoc queries', 'business user analytics', 'reduce engineering bottleneck'.
I'll help you build a self-serve analytics layer that empowers business stakeholders to find answers independently, reducing interrupt-driven analyst work.
.claude/data-stack-context.md for BI tool, team maturity, and non-technical stakeholder count.dbt parse to confirm the project is clean before adding new exposures.Why self-serve fails:
fct_orders, dim_sku_id)Why self-serve succeeds:
# In dbt — good column names for self-serve