Describe Uses and Application of IoT Tools DATA-ENGINEERING-OPTIMIZE Practice Questions (Page 3)

Questions 11–15

1. 11foundation · easy

   In an IoT architecture, which component typically aggregates data from multiple sensors and forwards it to a central system?

   • AStream processor
   • BGateway
   • CData lake
   • DDashboard
   Reveal Solution Discussion Select an answer first
2. 12expert · hard

   A manufacturing company uses IoT sensors on production lines. The data is ingested via MQTT and needs to be integrated with a Dell Data Lakehouse for analytics. The company wants to use the data for both real-time monitoring and historical analysis. The data engineering team is considering two options: (1) stream the MQTT data into a streaming platform and then write to the data lakehouse, or (2) write the MQTT data directly to the data lakehouse. Which option is more appropriate, and why?

   • AOption 2, because it is simpler and reduces latency
   • BOption 2, because the data lakehouse is optimized for streaming ingestion
   • COption 1, because it decouples ingestion from storage and allows for real-time processing
   • DOption 1, because the data lakehouse cannot store streaming data
   Reveal Solution Discussion Select an answer first
4. 13foundation · easy

   Which IoT analytics use case involves analyzing sensor data to predict when equipment is likely to fail?

   • AReal-time monitoring
   • BData visualization
   • COperational optimization
   • DPredictive maintenance
   Reveal Solution Discussion Select an answer first
5. 14foundation · easy

   A fleet of delivery trucks sends GPS coordinates every second. Which characteristic of IoT data is most directly demonstrated by this scenario?

   • AVeracity
   • BVolume
   • CVariety
   • DVelocity
   Reveal Solution Discussion Select an answer first
6. 15application · medium

   A retail chain uses IoT sensors to track foot traffic in stores. The data is ingested via MQTT and needs to be integrated with a Dell Data Lakehouse for analytics. The data engineering team wants to make the sensor data available for both real-time dashboards and historical reporting. Which integration approach is most effective?

   • AStore the MQTT data in a separate time-series database and export to the data lakehouse nightly
   • BIngest the MQTT data directly into the data lakehouse without any streaming platform
   • CStream the MQTT data into a streaming platform, then write to the data lakehouse for both real-time and batch analytics
   • DUse the data lakehouse only for batch analytics and a separate stream processing engine for real-time dashboards
   Reveal Solution Discussion Select an answer first