data-context-extractor

Extract tribal knowledge by capturing analyst insights on database schema, entity disambiguation, and key metrics to generate comprehensive reference files for company-specific data analysis skills. It supports connecting to data warehouses and discovering schema details automatically.

The best way to document database schema and key metrics is generating structured reference files that define tables, clarify entity relationships, and outline data hygiene rules. This organizes tribal knowledge into an accessible format for new analysts to query confidently.

Yes, you can improve an existing data analysis skill using Iteration Mode. This function enhances your current skill by extracting additional tribal knowledge, appending context for entity disambiguation, and updating reference files with new metrics or data hygiene rules.

You connect to a data warehouse and discover schema details using the built-in database connection and discovery features. This requires SQL dialect knowledge to map the database schema, identify tables, and extract structural relationships for your reference files.

Yes, SQL dialect knowledge and a deep understanding of your data domain are required. This prerequisite ensures you can accurately navigate the database schema, define key metrics, document data filtering rules, and identify common data hygiene pitfalls.

Generating reference files for tables, entities, and metrics preserves critical tribal knowledge. This process clarifies entity definitions, documents common pitfalls, and creates a comprehensive guide that standardizes how analysts interact with your company's data warehouse.