Generate complete, production-ready solutions for Dataverse SDK use cases with architecture guidance.

• Analyzes requirements across data volume, frequency, performance, and error tolerance to recommend appropriate patterns (transactional, batch, query, file management, scheduled, or real-time)
• Provides full Python implementation including authentication, singleton service classes, CRUD operations, bulk processing, and comprehensive error handling
• Includes data model design with table structures, relationships, and field definitions tailored to the specific use case
• Covers optimization strategies for high-volume operations, complex queries, and large file transfers with concrete code examples
• Delivers architecture documentation explaining design decisions, monitoring metrics, and testing patterns for production deployment