Correct Option: B. Support for both batch and stream processing within a unified model, enabling flexible data processing strategies: This is correct because Cloud Dataflow's ability to handle both batch and stream processing in a unified model directly addresses the team's need for flexibility in processing modes without requiring separate pipelines. This feature allows the team to efficiently manage real-time data for immediate insights and batch data for comprehensive reports under a single framework.

Incorrect Options: A. Seamless integration with Google Analytics for real-time data analysis: This is incorrect because while Cloud Dataflow can process data that may be used in Google Analytics, it does not directly integrate with Google Analytics for real-time analysis. C. Built-in data visualization tools for immediate insights from processed data: This is incorrect because Cloud Dataflow does not include built-in data visualization tools. Visualization would require integration with other services like Google Data Studio. D. Automatic encryption of all data at rest and in transit, ensuring compliance with security standards: This is incorrect because while data encryption is a critical feature, it is a standard across Google Cloud services and not a unique benefit of Cloud Dataflow.