TASK: Analytics Tool with NLP

Task Description Develop a basic NLP-powered query builder that allows users to write natural language queries and converts them into analytics tables. The system should use a rule-based parsing approach to interpret user intent, map keywords to the underlying database schema, and generate safe, validated SELECT queries. A query preview mechanism should allow users to review and confirm the generated SQL before execution. The design should be modular to support future ML-based or AI-driven enhancements.

Key Outcomes:

• Rule-based NLP parsing engine.
• Mapping logic between user keywords and database schema (tables, columns, relationships).
• Support for basic SELECT queries with WHERE conditions.
• Query preview before execution.
• SQL injection prevention mechanisms (strict validation and parameterized queries).
• Clear error handling and user-friendly feedback for unsupported or ambiguous queries.
• Modular and extensible architecture for future ML/NLP model integration.