A healthcare device manufacturer needs to ingest patient vital-sign data from wearable devices. The devices are battery-powered and connect over cellular networks. The data must be encrypted in transit and the ingestion must handle intermittent connectivity. The manufacturer also wants to perform real-time alerts for abnormal readings. Which ingestion approach is most suitable?

AMQP with mandatory TLS, feeding a message queue that is processed every hour

MQTT over TLS with QoS level 1, feeding a stream processing engine

Raw TCP sockets with custom encryption, feeding a stream processing engine

HTTP POST with JSON payloads over HTTPS, feeding a batch processing job

A hospital uses IoT devices to monitor patient heart rates and oxygen levels. The data is streamed to a central system. The hospital wants to detect critical events, such as a sudden drop in oxygen, and alert medical staff immediately. Which analytics approach is most appropriate?

Stream processing with real-time anomaly detection algorithms

Store all data in a data warehouse and run queries on demand

Use edge computing on each device to detect anomalies and send alerts

Batch processing every 15 minutes to analyze the data

A logistics company tracks delivery trucks with GPS devices that send location updates every 30 seconds. The company needs to provide live tracking to customers, but also needs to generate daily reports on fuel consumption and route efficiency. The data volume is moderate, and the company has limited compute resources. Which processing strategy is most efficient?

Use only batch processing for both live tracking and daily reports

Use stream processing for live tracking and batch processing for daily reports

Use edge computing on the trucks to process all data and send only summaries

Use only stream processing for both live tracking and daily reports

Dell Data Engineering Optimize

Domain 5Objective 1

Describe Uses and Application of IoT Tools DATA-ENGINEERING-OPTIMIZE Practice Questions (Page 5)

Part of the Processing Streaming and IoT Data domain, which accounts for 20% of the DATA-ENGINEERING-OPTIMIZE exam.

32questions here

7free pages

9concepts

20%of the exam

Questions 21–25

21application · medium
A healthcare device manufacturer needs to ingest patient vital-sign data from wearable devices. The devices are battery-powered and connect over cellular networks. The data must be encrypted in transit and the ingestion must handle intermittent connectivity. The manufacturer also wants to perform real-time alerts for abnormal readings. Which ingestion approach is most suitable?
Select an answer first
22foundation · easy
Which protocol is specifically designed for lightweight messaging in IoT environments and is commonly used for sensor data ingestion?
Select an answer first
23foundation · easy
Which governance consideration is most important when IoT data includes personal information about individuals?
Select an answer first
24application · medium
A hospital uses IoT devices to monitor patient heart rates and oxygen levels. The data is streamed to a central system. The hospital wants to detect critical events, such as a sudden drop in oxygen, and alert medical staff immediately. Which analytics approach is most appropriate?
Select an answer first
25application · medium
A logistics company tracks delivery trucks with GPS devices that send location updates every 30 seconds. The company needs to provide live tracking to customers, but also needs to generate daily reports on fuel consumption and route efficiency. The data volume is moderate, and the company has limited compute resources. Which processing strategy is most efficient?
Select an answer first

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Describe Uses and Application of IoT Tools DATA-ENGINEERING-OPTIMIZE Practice Questions (Page 5)

Questions 21–25

Which protocol is specifically designed for lightweight messaging in IoT environments and is commonly used for sensor data ingestion?

Which governance consideration is most important when IoT data includes personal information about individuals?

A hospital uses IoT devices to monitor patient heart rates and oxygen levels. The data is streamed to a central system. The hospital wants to detect critical events, such as a sudden drop in oxygen, and alert medical staff immediately. Which analytics approach is most appropriate?

Keep studying — Processing Streaming and IoT Data