1. What is the main purpose of data mining?
A) To store data effectively
B) To retrieve data from databases
C) To discover patterns in data
D) To clean and preprocess data
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2. Which of the following is a major issue in data mining?
A) Lack of structured data
B) Scalability and efficiency
C) Data visualization challenges
D) Limited storage space
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3. Which industry benefits the most from data mining applications?
A) Healthcare
B) Agriculture
C) Real estate
D) Entertainment
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4. Which of the following is a common data mining task?
A) Data storage
B) Data cleaning
C) Classification
D) Data integration
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5. What is predictive modeling in data mining?
A) Analyzing past data trends
B) Cleaning and filtering data
C) Storing large datasets
D) Using data to predict future outcomes
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6. Why is data cleaning important in data mining?
A) To improve data accuracy
B) To reduce storage requirements
C) To speed up data retrieval
D) To facilitate data visualization
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7. What is association rule learning?
A) A technique for predicting future outcomes
B) A method for discovering relationships between variables
C) A process for cleaning and integrating data
D) A task for categorizing data
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8. What is clustering in data mining?
A) Sorting data based on size
B) Classifying data into pre-defined categories
C) Grouping data points based on similarities
D) Cleaning and organizing data
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9. What is anomaly detection in data mining?
A) Identifying outliers in a dataset
B) Grouping similar data points together
C) Predicting future trends
D) Visualizing data in graphs
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10. Which algorithm is commonly used in data mining for classification?
A) Linear regression
B) K-means clustering
C) Naive Bayes
D) Decision trees
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11. What are the key characteristics of big data?
A) Small size and simplicity
B) Volume, variety, velocity, and veracity
C) Low storage requirements
D) Uniformity of data
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12. Which technology is widely used for big data processing?
A) Hadoop
B) SQL
C) JavaScript
D) Excel
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13. What is data warehousing?
A) The process of deleting old data
B) A method for data visualization
C) Storing data in a centralized repository
D) A way to clean data
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14. What is a data lake?
A) A type of database
B) A storage repository for raw data
C) A data cleaning tool
D) A data visualization software
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15. How does data mining benefit businesses?
A) By generating actionable insights
B) By increasing data storage costs
C) By reducing data quality
D) By complicating data analysis
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16. What is the role of data visualization in data mining?
A) To hide data complexity
B) To increase data storage needs
C) To complicate data analysis
D) To present findings in an understandable manner
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17. In which sector is data mining particularly useful for fraud detection?
A) Education
B) Agriculture
C) Finance
D) Real estate
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18. Which machine learning model is known for its effectiveness in classification tasks?
A) Decision Trees
B) Support Vector Machines
C) K-Means Clustering
D) Linear Regression
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19. What is the purpose of outlier detection in data preprocessing?
A) To reduce data storage
B) To speed up computation
C) To identify and manage anomalous data points
D) To enhance data quality
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20. What does data wrangling refer to in the context of data science?
A) Data storage optimization
B) Cleaning and transforming raw data
C) Data visualization techniques
D) Data analysis methods
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