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Create a Wren MDL project, a model layer for database queries, from an existing database. Discover tables and relationships, normalize column types, generate YAML files, and validate and build the project before indexing its schema.

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• Create a Wren project from an existing database
• Add selected schemas and tables as a new data source
• Define model relationships from database constraints

Answer business data questions with Wren CLI by checking model definitions, reusing past queries, and executing SQL or predefined aggregations. The workflow also covers query verification, error diagnosis, and saving successful queries for future use.

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• Analyze monthly revenue trends
• Rank customers by purchase value
• Compare metrics across plans or regions

Set up Wren Engine through guided steps covering environment checks, installation, database connection, and project creation. Prepare data definitions and validate the setup, then suggest initial questions to help the user begin exploring their data.

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• Installing Wren Engine for the first time
• Connecting a new database to Wren
• Creating a project and preparing data definitions

Import SaaS data into DuckDB using dlt, a data loading tool, then generate a Wren project with table definitions and relationships. Verify the setup with real SQL queries, or start from an existing DuckDB file.

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• Importing HubSpot or Stripe data for SQL analysis
• Creating a Wren project from an existing dlt DuckDB file
• Generating table definitions and parent-child relationships

Find the Wren CLI workflow for answering data questions, connecting databases or SaaS sources, generating model definitions, adding business metrics, or building a shareable analytics app. Guides are retrieved from the installed CLI version.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Set up Wren and connect a database
• Load HubSpot or Stripe data through dlt
• Generate model definitions and add business metrics

Add business knowledge missing from a Wren project's database definitions. Compare source documents with existing context, then add explanations, rules, SQL examples, and proposed metrics through guided questions or an automatic mode with an audit report.

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• Documenting status codes, units, and NULL meanings
• Adding business knowledge from handbooks and glossaries
• Defining aggregation metrics such as ARR or DAU

Build an analytics web app from a Wren project's data definitions and business context. Create charts and tables, validate the app, and deploy to Vercel or Cloudflare with a checked URL for sharing.

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• Building a sales dashboard from a Wren project
• Sharing a report with bundled data
• Creating an analytics app that fetches current data