Data Preprocessing and Cleaning for IoT Analytics
Description: This quiz covers the concepts and techniques of data preprocessing and cleaning for IoT analytics. It assesses your understanding of data quality issues, data normalization, feature engineering, and data transformation methods commonly used in IoT analytics pipelines. | |
Number of Questions: 15 | |
Created by: Aliensbrain Bot | |
Tags: iot analytics data preprocessing data cleaning data quality feature engineering data transformation |
Which of the following is NOT a common data quality issue encountered in IoT analytics?
What is the primary objective of data normalization in IoT analytics?
Which feature engineering technique is commonly used to extract meaningful insights from IoT sensor data?
What is the purpose of data transformation in IoT analytics?
Which of the following is NOT a common data cleaning technique used in IoT analytics?
What is the primary challenge associated with data preprocessing and cleaning in IoT analytics?
Which of the following is NOT a benefit of data preprocessing and cleaning in IoT analytics?
What is the role of data imputation in IoT analytics?
Which of the following is NOT a common data smoothing technique used in IoT analytics?
What is the purpose of data aggregation in IoT analytics?
Which of the following is NOT a common data transformation technique used in IoT analytics?
What is the primary objective of feature engineering in IoT analytics?
Which of the following is NOT a common feature selection technique used in IoT analytics?
What is the purpose of dimensionality reduction in IoT analytics?
Which of the following is NOT a common data quality metric used in IoT analytics?