ExpertHard1 markMultiple Choice
AZ-305 · Question 24 · Domain 2.2: Design Data Integration
You are designing a real-time fraud detection system for a financial services company.
Millions of credit card transactions per minute will be ingested. The system must evaluate these transactions against a machine learning model in real-time. Transactions flagged as fraudulent must be sent to a Service Bus queue for immediate human review. All raw transactions must be archived to Azure Data Lake Storage Gen2 for future model training.
Which TWO Azure services should you include in the data integration architecture? (Select TWO)
You are designing a real-time fraud detection system for a financial services company.
Millions of credit card transactions per minute will be ingested. The system must evaluate these transactions against a machine learning model in real-time. Transactions flagged as fraudulent must be sent to a Service Bus queue for immediate human review. All raw transactions must be archived to Azure Data Lake Storage Gen2 for future model training.
Which TWO Azure services should you include in the data integration architecture? (Select TWO)
Answer options:
A.
Azure Event Hubs
B.
Azure Data Factory
C.
Azure Stream Analytics
D.
Azure Event Grid
E.
Azure SQL Managed Instance
How to approach this question
High throughput ingestion = Event Hubs. Real-time processing/routing/ML integration = Stream Analytics.
Full Answer
Azure Event Hubs, Azure Stream Analytics
Azure Event Hubs is designed to ingest massive streams of telemetry data (millions of events/sec). Azure Stream Analytics connects to Event Hubs to process the data in real-time. Stream Analytics has built-in capabilities to call Azure Machine Learning endpoints, output specific records to Service Bus, and simultaneously output all raw data to Azure Data Lake Storage.
Common mistakes
Confusing Event Hubs (telemetry streaming) with Event Grid (discrete event routing).
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