Schema Mapping (Semantic Context)

Concept

Schema mapping is the process of providing explicit semantic definitions, relationships, and business logic for database tables and columns so users and AI agents query them correctly.

Layman Explanation & Analogy

Think of schema mapping as a bilingual dictionary between human business terms and cryptic database column names. To a human, "revenue" is simple. But in a database, is revenue in `orders.total_price`, `invoices.subtotal`, or `transactions.gross_amt`? Schema mapping teaches query tools and AI models exactly what each column means and how tables connect.

Worked real-world example

Mapping the column `rev_usd_net` in the `fact_sales` table as the primary source for "Company Net Revenue (excluding discounts and sales tax)".

What people get wrong & common traps

Writing correct SQL syntax is easy for AI; knowing which of five similar tables contains the true financial metric is the hard part. Without proper schema mapping, AI tools will write syntactically perfect queries that calculate completely wrong numbers.

Related terms