Best Practices for SQL Query Generation with Infoworks AI

Leveraging Infoworks AI for SQL query generation enhances data retrieval and data processing functionalities. To maximize the effectiveness of this feature, consider the following best practices:

• Be Specific: Provide clear and concise descriptions of the required data retrieval or manipulation tasks.
• Familiarize with the Schema: Understanding the database schema enhances the formulation of effective business requirements.
• Utilize Chat History: Review past queries to inform and improve future interactions.
• Provide Detailed Context: If a query is part of a larger task, providing context aids in generating more accurate SQL.
• Specify Conditions Explicitly: Clearly state any conditions in queries (e.g., specify a date range instead of using vague terms like "recent data").
• Mention Aggregations: Clearly identify any necessary aggregations, such as sums or averages, and specify the attributes involved.
• Clarify Table Relationships: If multiple tables are involved, articulate their relationships, ideally through primary and foreign keys.
• Indicate Result Requirements: Specify the desired order of results or any row limitations.
• Avoid Ambiguity: Eliminate ambiguous terms and vague descriptions to prevent incorrect SQL generation.
• One Query at a Time: Focus on a single piece of information per query to maintain clarity.
• Use Consistent Terminology: Utilize the exact terminology from the database schema when referring to specific entities.
• Provide Examples: When applicable, include examples of expected output to clarify intent.
• Request Aliases and Formatting: For shared or reused SQL queries, request the inclusion of aliases for tables and formatting for better readability.
• Rephrase if Necessary: If the generated SQL does not meet requirements, rephrase the question or provide additional context.
• Review AI Responses: Scrutinize the AI's explanations and generated SQL to ensure alignment with requests, and ask follow-up questions for clarity.
• Test Generated Code: Validate the correctness of generated SQL in a safe environment before deploying it in a production database.