IOT IoT Data Analytics 1 — Questions and Answers
Question 1: What is 'time-series data' in the context of IoT analytics?
- Data sorted alphabetically by device name
- Sequential data points collected over time from IoT sensors, indexed by timestamp (Correct answer)
- Data organized by geographic location
- Encrypted data streams from IoT devices
Correct answer: Sequential data points collected over time from IoT sensors, indexed by timestamp
Time-series data consists of sequential IoT sensor readings timestamped at regular intervals, capturing how values change over time.
Question 2: Which type of IoT analytics uses historical data to identify what happened and why?
- Predictive analytics
- Prescriptive analytics
- Descriptive analytics (Correct answer)
- Cognitive analytics
Correct answer: Descriptive analytics
Descriptive analytics analyzes historical IoT data to summarize past events, answer 'what happened' and 'why it happened'.
Question 3: What is anomaly detection in IoT data analytics used for?
- Compressing IoT data for storage
- Identifying data points that deviate significantly from expected patterns, indicating potential failures or security threats (Correct answer)
- Encrypting sensor readings
- Scheduling device maintenance manually
Correct answer: Identifying data points that deviate significantly from expected patterns, indicating potential failures or security threats
Anomaly detection algorithms identify unusual patterns in IoT sensor data that could indicate equipment failures, security breaches, or process deviations.
Question 4: Which database type is most commonly used to store and query large volumes of IoT time-series sensor data?
- Relational SQL database
- Document store
- Time-series database (TSDB) (Correct answer)
- Graph database
Correct answer: Time-series database (TSDB)
Time-series databases like InfluxDB or TimescaleDB are optimized for storing, retrieving, and analyzing timestamped IoT sensor data at scale.
Question 5: What does 'data aggregation' mean in an IoT analytics pipeline?
- Deleting redundant IoT data
- Combining data from multiple IoT devices or sensors into a unified dataset for analysis (Correct answer)
- Encrypting data before transmission
- Routing data to different cloud regions
Correct answer: Combining data from multiple IoT devices or sensors into a unified dataset for analysis
Data aggregation collects and combines sensor readings from multiple IoT devices into a consolidated dataset to enable broader analysis.
Question 6: Which machine learning technique is commonly used in IoT predictive maintenance to forecast equipment failure?
- K-means clustering
- Reinforcement learning
- Regression analysis and classification models (Correct answer)
- Generative adversarial networks (GANs)
Correct answer: Regression analysis and classification models
Regression analysis and classification models are widely used in IoT predictive maintenance to predict when equipment will fail based on sensor patterns.
IOT IoT Data Analytics 1
What is 'time-series data' in the context of IoT analytics?