AI2sql Docs
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  • 1. Introduction
    • 1.1. What is AI2SQL?
    • 1.2. Key features of AI2SQL
    • 1.3. How to get started with AI2SQL
    • 1.4. What Users Can Ask AI2SQL
  • 2. AI2SQL Dashboard
    • 2.1. Accessing the dashboard
    • 2.2. Generating SQL based on predefined datasets
    • 2.3. Exploring sample queries and use cases
  • 3. Managing Tables
    • 3.1. Importing tables using DDL
    • 3.2. Manually adding tables
    • 3.3. Editing, Updating, and Deleting Table Information
    • 3.4. Importing Database Schema via CSV
  • 4. AI2SQL Workspace
    • 4.1. Navigating the workspace
    • 4.2. Generating SQL for specific database engines
    • 4.3. Selecting tables for SQL generation
    • 4.4. Saving and organizing queries in the workspace
  • 5. Formatting SQL
    • 5.1. Accessing the SQL formatter
    • 5.2. Customizing formatting options
    • 5.3. Applying formatting to your SQL queries
  • 6. SQL Fixer
    • 6.1. Identifying SQL errors with SQL Fixer
    • 6.2. Understanding common SQL error messages
    • 6.3. Resolving SQL errors using AI2SQL's suggestions
    • 6.4. Handling Long SQL Queries
  • 7. Formula Generator
    • 7.1. Overview of Formula Generator
    • 7.2. Excel, Google Sheets, and regex formula translation
    • 7.3. Power BI DAX formula translation
    • 7.4. Airtable formula translation
    • 7.5. Using Formula Generator to enhance SQL queries
  • 8. CSV Analyzer
  • 9. Database Connectors
    • 9.1. Supported database connectors
    • 9.2. Setting up database connections (MySQL, SQL Server, or PostgreSQL)
    • 9.2.1. AI2sql Oracle Cloud Connector
    • 9.3. Setting up MongoDB Connectors
    • 9.4. Google BigQuery Setup and Service Account Key Creation
    • 9.5. Generating SQL queries for connected databases
    • 9.6. Setting up Snowflake Connectors
    • 9.7. Troubleshooting AI2sql Connector Issues: A Comprehensive Checklist
    • 9.8. Requesting new database connectors
    • 9.9. System Security Overview
  • 10. Dataset Questions Generation
  • 11. AI2SQL ChatGPT Plugin User Guide
    • 11.1. Introduction
    • 11.2. Getting Started
    • 11.3. Obtaining Your Token
    • 11.4. Using Your Token
    • 11.5. Connecting Your MSSQL (SQL Server) Database
    • 11.6. Connecting Your MySQL Database
    • 11.7. Connecting Your PostgreSQL Database
    • 11.8. Generating SQL Queries
    • 11.9. Troubleshooting
  • 12. Troubleshooting and Support
    • 9.1. Common issues and solutions
    • 12.2. Chat Support
    • 12.3. Contacting AI2SQL support
    • 12.4. Community resources and forums
  • 13. Templates
    • 13.1. Custom Template Creation
    • 13.2. Save the Template
    • 13.3. Generate SQL Using Template
  • 14. AI2sql: SQL Generation from Database ER Diagrams
    • 14.1. Introduction
    • 14.2. SQL Generation Process
    • 14.3. Troubleshooting & FAQs
  • 15. AI2sql API Integration
  • 16. AI2SQL Dictionary Template
  • 17. AI2sql GPTs
    • 17.1. Getting Started
    • 17.2. Obtaining Your Token
    • 17.3. Connecting Your MySQL Database
  • 18. Connecting Your Local Database
  • 19. SQL File Uploader
    • 19.1 Generating SQL queries
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On this page
  • Introduction
  • General Information
  • Schema Mapping
  • Business Logic Rules
  • Synonyms and Aliases
  • Special Cases and Exceptions
  • Change Log

16. AI2SQL Dictionary Template

Introduction

This document is an AI to SQL Dictionary template, designed to facilitate the mapping of natural language terms to SQL schema elements for any database. This guide is intended for data analysts, developers, and database administrators to improve query efficiency and understanding of the database structure.


General Information

  • Dictionary Name: [Dictionary Name]

  • Creation Date: [Creation Date]

  • Version: [Version Number]

  • Author: [Author Name]

  • Description: A comprehensive dictionary for mapping natural language terms to SQL schema elements in [Database Name].


Schema Mapping

This section should detail the mapping of natural language terms to their corresponding SQL tables, columns, and relationships in the database.

Tables

Mapping of general terms to specific SQL table names.

Natural Language Term
SQL Table Name

[Term]

[TableName]

[Term]

[TableName]

Columns

Mapping of general terms to specific SQL column names.

Natural Language Term
SQL Column Name

[Term]

[ColumnName]

[Term]

[ColumnName]

Relationships

Describing the relationships between different tables and columns.

Natural Language Description
SQL Relationship Expression

[Description]

[SQL Expression]


Business Logic Rules

Describe specific business logic rules applied within the database.

Rule ID
Description
Natural Language Expression
SQL Expression

[ID]

[Description]

[Natural Language Term]

[SQL Expression]


Synonyms and Aliases

List synonyms and aliases for natural language terms to aid in query formulation.

Natural Language Term
Synonyms/Aliases

[Term]

[Synonyms]


Special Cases and Exceptions

Detail how to handle unique or unusual cases within the database.

  • Case ID: [ID]

  • Description: [Description]

  • Handling Instructions: [Instructions]


Change Log

Document the history of changes made to the dictionary.

  • [Date]: [Change Description]


This template can be customized for any database by filling in specific details related to the database schema, business rules, and terminology. It's important to keep this document updated to reflect any changes in the database structure or business logic.

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Last updated 1 year ago