Text-to-SQL
Using a language model to translate a question in plain English into a database query, run it and return the result. It lets people who do not write SQL ask questions of structured data directly.
Why it matters
Text-to-SQL promises faster access to data, but a query that runs is not necessarily a query that is right. Ambiguous business terms, complex joins and inconsistent metric definitions all lead to plausible but incorrect answers.
Reliable implementations constrain the model to a governed semantic layer or curated views, show the query and definitions used, respect row-level permissions and are evaluated against a set of known questions.
In practice
For example, a UK multi-site retailer might let area managers ask ‘which stores missed their weekly sales target’ through a text-to-SQL assistant that queries only certified sales views, displays the metric definition and logs every generated query.
Where Rodan fits
Rodan connects natural-language analytics to governed metrics in Analytics and Intelligence work. See also what is structured data injection and when should you use it instead of RAG.