Tiêu đề mcq DATA SCIENCES_ DATA WAREHOUSING AND DATA MINING.pdf ✅

Way to Polytechnic ● Way to Polytechnic DATA SCIENCES: DATA WAREHOUSING AND DATA MINING Unit – 1 Introduction : 1. What is the primary motivation behind data mining? A) To collect large volumes of data B) To extract useful information and patterns from data C) To encrypt data for security purposes D) To delete unnecessary data Answer: B) To extract useful information and patterns from data 2. Why is data mining important in modern contexts? A) To reduce data storage costs B) To improve decision-making processes C) To increase data complexity D) To limit data access Answer: B) To improve decision-making processes 3. What is data mining, in essence? A) Extracting gold from data B) Extracting valuable patterns and information from large datasets C) Extracting raw data for processing D) Deleting irrelevant data from datasets Answer: B) Extracting valuable patterns and information from large datasets 4. What kinds of data are typically involved in data mining? A) Structured data only B) Unstructured data only C) Both structured and unstructured data D) No data is involved in data mining Answer: C) Both structured and unstructured data 5. Which of the following is NOT a data mining functionality? A) Clustering B) Classification C) Data deletion D) Association Answer: C) Data deletion 1
Way to Polytechnic ● Way to Polytechnic 6. What are the two main kinds of patterns that data mining extracts? A) Simple and complex patterns B) Predictive and descriptive patterns C) High-dimensional and low-dimensional patterns D) Structured and unstructured patterns Answer: B) Predictive and descriptive patterns 7. How are data mining systems classified based on the kind of knowledge mined? A) By the nature of algorithms used B) By the volume of data processed C) By the kind of patterns mined D) By the speed of processing Answer: C) By the kind of patterns mined 8. What are Data Mining Task Primitives? A) Fundamental operations in data mining algorithms B) Basic principles of data preprocessing C) Specific data mining techniques D) Types of data visualization Answer: A) Fundamental operations in data mining algorithms 9. What is the integration of a data mining system with a database or data warehouse system called? A) Data fusion B) Data migration C) Data transformation D) Online Analytical Processing (OLAP) Answer: D) Online Analytical Processing (OLAP) 10. What are the major issues in data mining? A) Data privacy and security B) Data redundancy and duplication C) Data compression and storage D) Data deletion and archiving Answer: A) Data privacy and security 2
Way to Polytechnic ● Way to Polytechnic 11. What are the types of data sets and attribute values commonly encountered in data mining? A) Numeric and categorical B) Textual and visual C) Dynamic and static D) Qualitative and quantitative Answer: A) Numeric and categorical 12. What is the purpose of data preprocessing in data mining? A) To increase the complexity of the dataset B) To reduce data storage costs C) To improve data quality and prepare it for mining D) To add noise to the dataset Answer: C) To improve data quality and prepare it for mining 13. What are the major tasks in data preprocessing? A) Data extraction and visualization B) Data compression and encryption C) Data cleaning and integration D) Data deletion and archiving Answer: C) Data cleaning and integration 14. What is data reduction in data preprocessing? A) Increasing the size of the dataset B) Decreasing the size of the dataset while preserving important information C) Deleting irrelevant data D) Duplicating data for redundancy Answer: B) Decreasing the size of the dataset while preserving important information 15. What does data transformation involve? A) Converting data into a different format suitable for mining B) Deleting data C) Encrypting data for security D) Increasing data complexity Answer: A) Converting data into a different format suitable for mining 16. What is data discretization in data preprocessing? A) The process of converting continuous data into categorical data B) The process of converting categorical data into continuous data C) The process of deleting data 3
Way to Polytechnic ● Way to Polytechnic D) The process of compressing data Answer: A) The process of converting continuous data into categorical data 17. What is data cleaning in data preprocessing? A) Adding noise to the dataset B) Reducing data size C) Removing noisy or irrelevant data from the dataset D) Converting data into a different format Answer: C) Removing noisy or irrelevant data from the dataset 18. How is data integration performed in data preprocessing? A) By adding new data sources to the dataset B) By combining data from multiple sources into a single dataset C) By deleting redundant data D) By compressing the dataset Answer: B) By combining data from multiple sources into a single dataset 19. What is meant by measuring data similarity? A) Comparing data attributes B) Deleting similar data C) Adding noise to the dataset D) Measuring data storage Answer: A) Comparing data attributes 20. What is data visualization in data mining? A) The process of transforming data into visual representations B) Deleting data C) Adding noise to the dataset D) Measuring data complexity Answer: A) The process of transforming data into visual representations 4