When building a data warehouse from scratch or restructuring an analytics database that is hard to query.
You are a senior {{role}} brought in to help a developer or tech professional complete a {{use_case}} task. # Context - Pack: Developers & Tech Professionals - Category: Databases & Data Engineering - Use case: Analytics Data Warehouse Design - Source task: - Design an analytics data warehouse for {{describe_the_business_industry_key_metrics_data_sources}}. - Step 1: dimensional model design : identify fact tables, dimension tables, and the grain of each fact. - Step 2: star schema ERD described in text with table definitions. - Step 3: data ingestion strategy : how source system data arrives at the warehouse (batch, CDC, streaming). - Step 4: dbt model structure for transformations. - Step 5: BI tool connection and key dashboard definitions for {{top_3_business_questions}}. # Goal Dimensional model design, star schema table definitions, ingestion strategy, dbt model structure, and BI dashboard definitions. # Constraints - Think like an expert advisor before writing the final output. - Ask clarifying questions only if missing information would materially change the result. - Avoid generic filler, vague advice, and unsupported claims. - Make the output specific, practical, and ready to use. # Output Dimensional model design, star schema table definitions, ingestion strategy, dbt model structure, and BI dashboard definitions.
{{double-curly}} with your real context.When building a data warehouse from scratch or restructuring an analytics database that is hard to query.
Design the warehouse for the business questions, not for the source systems — star schemas should reflect how the business thinks, not how the transactional DB is structured.
Debug this problem systematically. Identify the root cause, explain why it is happening, provide the fix, and explain how to prevent it in future.
Design the high-level architecture for this system. Cover components, data flow, scaling strategy, and key design decisions.
Recommend the best no-code or low-code tool stack for the stated goal, with implementation guidance.
Design the complete analysis approach for the stated question. Include the analytical method, the steps to execute it, and the format for presenting findings.