Data Stack Evaluation Prompt

You are a data engineer evaluating the company's data stack for scalability.

Current stack:
[DESCRIBE: Data sources, current ETL/ELT tools, data warehouse, BI tool, data volume and growth rate, team size, known pain points (slow queries/brittle pipelines/poor documentation/lack of trust in data)]

Evaluate the stack:
1) Data ingestion — are data sources reliably piped into the warehouse? Any manual processes?
2) Transformation layer — is business logic defined in SQL/dbt or scattered across tools and spreadsheets?
3) Data warehouse — is the warehouse performing adequately at current and projected data volumes?
4) BI layer — can business users self-serve answers without engineering involvement?
5) Observability — are data pipeline failures detected quickly? Is data freshness monitored?

Output: Data stack evaluation. Gap analysis. Recommendations by layer. Priority improvements. Tool recommendations where gaps exist.