Q.1 What is the main purpose of IoT data management?
To connect IoT devices
To secure IoT hardware
To collect, store, and process IoT data
To design IoT sensors
Explanation - IoT data management focuses on handling large volumes of data generated by IoT devices by collecting, storing, and processing them efficiently.
Correct answer is: To collect, store, and process IoT data
Q.2 Which of the following is a common data storage solution for IoT?
Data warehouse
Relational databases only
NoSQL databases
Spreadsheet
Explanation - NoSQL databases are commonly used in IoT because they handle large amounts of unstructured and semi-structured data efficiently.
Correct answer is: NoSQL databases
Q.3 Which characteristic of IoT data makes real-time analytics important?
Small size
Batch-oriented nature
High velocity
Manual processing
Explanation - IoT data is generated rapidly in streams, so real-time analytics is required to process high-velocity data instantly.
Correct answer is: High velocity
Q.4 What is edge computing in IoT?
A method of storing IoT data in the cloud
Processing data at the device or near the source
Sending all data to centralized servers
Visualizing IoT data
Explanation - Edge computing processes data close to the source of generation, reducing latency and network load.
Correct answer is: Processing data at the device or near the source
Q.5 Which of these is NOT an IoT analytics technique?
Descriptive analytics
Prescriptive analytics
Predictive analytics
Organic analytics
Explanation - Descriptive, predictive, and prescriptive analytics are standard in IoT, while 'organic analytics' is not a recognized category.
Correct answer is: Organic analytics
Q.6 In IoT, what does 'data ingestion' mean?
Analyzing stored data
Transferring data from devices to storage/processing systems
Cleaning invalid data
Visualizing data
Explanation - Data ingestion refers to the process of collecting and transporting data from IoT devices into storage or analytics systems.
Correct answer is: Transferring data from devices to storage/processing systems
Q.7 Why is scalability important in IoT data management?
IoT devices rarely generate data
IoT data volume grows rapidly with devices
IoT systems use only one database
IoT analytics needs low complexity
Explanation - As more IoT devices are deployed, data volume increases, requiring scalable systems to handle growing workloads.
Correct answer is: IoT data volume grows rapidly with devices
Q.8 Which protocol is commonly used for IoT data transmission?
SMTP
HTTP
MQTT
FTP
Explanation - MQTT is a lightweight publish-subscribe protocol widely used in IoT for efficient communication.
Correct answer is: MQTT
Q.9 What does 'data cleansing' in IoT analytics involve?
Removing duplicate and invalid data
Storing data in the cloud
Encrypting IoT data
Creating dashboards
Explanation - Data cleansing ensures the data is accurate, consistent, and usable by eliminating errors and duplicates.
Correct answer is: Removing duplicate and invalid data
Q.10 Which type of IoT data storage is best suited for structured queries?
NoSQL
SQL databases
File system storage
Blockchain
Explanation - SQL databases are best suited for structured queries, making them useful for certain types of IoT applications.
Correct answer is: SQL databases
Q.11 What is stream processing in IoT analytics?
Processing data in small batches
Processing continuous real-time data flows
Compressing IoT data
Archiving old data
Explanation - Stream processing deals with analyzing data as it flows in real-time rather than waiting for batch storage.
Correct answer is: Processing continuous real-time data flows
Q.12 Which of the following is a cloud platform commonly used for IoT analytics?
AWS IoT Core
Linux Kernel
MATLAB
Windows IoT
Explanation - AWS IoT Core is a cloud platform that supports IoT device connectivity, data management, and analytics.
Correct answer is: AWS IoT Core
Q.13 What role does machine learning play in IoT analytics?
Only data storage
Predicting trends and automating decisions
Encrypting data
Replacing sensors
Explanation - Machine learning analyzes IoT data to predict outcomes and enable automated decision-making.
Correct answer is: Predicting trends and automating decisions
Q.14 Which challenge is unique to IoT data management compared to traditional systems?
Data security
High data volume and velocity
Software bugs
Lack of users
Explanation - While security and bugs are general challenges, IoT specifically deals with the complexity of handling fast and massive data streams.
Correct answer is: High data volume and velocity
Q.15 What is the main advantage of using time-series databases in IoT?
Low memory usage
Efficient handling of data indexed by time
Supports only structured data
Unlimited storage
Explanation - Time-series databases are optimized for managing data with timestamps, which is common in IoT sensor data.
Correct answer is: Efficient handling of data indexed by time
Q.16 Which IoT data format is lightweight and widely used for communication?
CSV
JSON
XML
YAML
Explanation - JSON is lightweight and human-readable, making it a popular choice for IoT communication.
Correct answer is: JSON
Q.17 What is a data lake in IoT?
A structured database
A centralized repository storing raw data of all types
A water-cooled data center
An algorithm for data mining
Explanation - Data lakes store raw IoT data (structured, semi-structured, and unstructured) for flexible future processing.
Correct answer is: A centralized repository storing raw data of all types
Q.18 Which visualization tool is commonly used for IoT analytics dashboards?
Tableau
GIMP
Photoshop
Eclipse
Explanation - Tableau is widely used for creating interactive dashboards that visualize IoT analytics.
Correct answer is: Tableau
Q.19 Why is data compression important in IoT?
To make visualization easy
To reduce storage and bandwidth requirements
To prevent hacking
To improve graphics
Explanation - Data compression helps IoT systems handle large amounts of data more efficiently by reducing storage and transmission costs.
Correct answer is: To reduce storage and bandwidth requirements
Q.20 Which technique helps in predicting future IoT system failures?
Descriptive analytics
Predictive analytics
Prescriptive analytics
Diagnostic analytics
Explanation - Predictive analytics uses historical data patterns to forecast possible future events, such as equipment failures.
Correct answer is: Predictive analytics
Q.21 Which component ensures security of IoT data during transmission?
Firewalls
Encryption
Visualization
Compression
Explanation - Encryption ensures that IoT data remains secure and protected from unauthorized access during transmission.
Correct answer is: Encryption
Q.22 What is the purpose of metadata in IoT data management?
Stores user passwords
Describes characteristics of data
Deletes old data
Encrypts data
Explanation - Metadata provides context such as time, source, and format of IoT data, helping in efficient data management.
Correct answer is: Describes characteristics of data
Q.23 Which cloud service model is commonly used for IoT analytics?
IaaS
PaaS
SaaS
All of the above
Explanation - IoT analytics can be implemented using IaaS, PaaS, and SaaS depending on the system design and requirements.
Correct answer is: All of the above
Q.24 What is the biggest reason traditional databases struggle with IoT data?
Lack of security
High velocity and unstructured formats
High hardware cost
Limited visualization tools
Explanation - Traditional databases are not designed for the massive, fast, and varied data formats generated in IoT systems.
Correct answer is: High velocity and unstructured formats
Q.25 What is anomaly detection in IoT analytics?
Finding duplicate values
Identifying unusual patterns in data
Encrypting IoT data
Reducing data latency
Explanation - Anomaly detection identifies outliers or abnormal behaviors in IoT systems, helping in fault detection and security.
Correct answer is: Identifying unusual patterns in data