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You are designing a solution for a financial services company that requires real-time analytics on high-volume streaming data to detect fraudulent transactions immediately. The solution must scale dynamically with the data volume, support complex event processing, and integrate seamlessly with other Google Cloud services for data ingestion and storage. Given these requirements, which Google Cloud service is BEST optimized for real-time analytics on streaming data in this scenario? Choose the most appropriate option.
A
Cloud Data Fusion: A fully managed, cloud-native data integration service that helps users build and manage ETL/ELT pipelines.
B
Cloud Pub/Sub: A messaging service for sending and receiving messages between independent applications, designed for event ingestion and delivery.
C
BigQuery: A serverless, highly scalable, and cost-effective multi-cloud data warehouse designed for business agility, with real-time analytics capabilities.
D
Cloud Dataflow: A fully managed service for transforming and enriching data in stream (real-time) and batch (historical) modes, with autoscaling and complex event processing capabilities.
E
Both BigQuery and Cloud Dataflow: Combining the real-time analytics capabilities of BigQuery with the stream processing power of Cloud Dataflow for comprehensive real-time data analysis.