The trigger scheduling options are decently robust.
Azure Data Factory provides seamless integration with various data sources and supports data transformation, offering scalability and reliability for growing business needs. Built-in connectors streamline processes, while a low code/no code environment enhances user accessibility. However, the platform needs a more intuitive scheduler and improved integration with third-party systems. Additionally, it faces challenges with complex documentation and pricing models, while requiring optimization for performance, especially in parallel processing and workload scaling.
