IOT IoT Data Analytics 2

Question 1

What is 'edge analytics' in an IoT deployment?

Accepted Answer

Processing and analyzing IoT data at or near the device rather than sending it all to the cloud

Answer

Edge analytics processes IoT data locally on edge devices or gateways, reducing latency and bandwidth by analyzing data before it reaches the cloud.

Question 2

Which concept describes the practice of processing only significant IoT data changes rather than transmitting every reading?

Accepted Answer

Delta transmission or exception reporting

Answer

Delta transmission or exception reporting only sends IoT data when values change beyond a threshold, reducing bandwidth and storage requirements.

Question 3

What is the purpose of a 'digital twin' in IoT data analytics?

Accepted Answer

A virtual model of a physical IoT device or system, updated with real-time sensor data for simulation and analysis

Answer

A digital twin is a virtual representation of a physical IoT system continuously updated with real-time data, enabling simulation, monitoring, and predictive analysis.

Question 4

Which streaming analytics platform is commonly used to process high-volume, real-time IoT data streams?

Accepted Answer

Apache Kafka with Kafka Streams or Apache Flink

Answer

Apache Kafka with Kafka Streams or Apache Flink are popular platforms for ingesting and processing high-throughput real-time IoT data streams.

Question 5

What does 'data normalization' mean when preparing IoT sensor data for analytics?

Accepted Answer

Scaling data values to a standard range to remove bias due to different measurement units

Answer

Data normalization scales IoT sensor readings to a common range so that variables with different units don't disproportionately influence analytics models.

IOT - Internet of Things Practice Test

IOT - Internet of Things Practice Test

IOT IoT Data Analytics 2