Introduction to Big Data MCQs with Answers

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Q1. What is Big Data?
a) Small collection of data stored in spreadsheets
b) Extremely large and complex datasets that cannot be handled by traditional processing methods
c) Printed records stored in files
d) Numerical data only

Q2. Which of the following is NOT a major source of Big Data?
a) Transactional Data
b) Machine Data
c) Social Data
d) Printed Newspapers

Q3. Online shopping transactions are an example of:
a) Machine Data
b) Transactional Data
c) Social Data
d) Unstructured Data

Q4. Which company was mentioned as using Big Data for recommendation systems?
a) Amazon
b) Adobe
c) Oracle
d) Intel

Q5. A shopkeeper analyzing daily sales to restock products is an example of:
a) Big Data
b) Small Data
c) Cloud Data
d) Metadata

Q6. Which type of data has a predefined schema?
a) Structured Data
b) Semi-Structured Data
c) Unstructured Data
d) Multimedia Data

Q7. JSON and XML files are examples of:
a) Structured Data
b) Semi-Structured Data
c) Unstructured Data
d) Machine Data

Q8. Which of the following is an example of Unstructured Data?
a) Customer database
b) CSV file
c) Social media posts
d) Product catalog

Q9. Which type of data is easiest to search and analyze?
a) Structured Data
b) Semi-Structured Data
c) Unstructured Data
d) Multimedia Data

Q10. Big Data primarily helps organizations by:
a) Increasing paperwork
b) Improving decision-making
c) Eliminating databases
d) Reducing internet speed

Q11. Which advantage of Big Data enables organizations to understand customer preferences?
a) Better Customer Insights
b) Technical Complexity
c) Privacy Concerns
d) Regulatory Compliance

Q12. Identifying market trends before competitors is an example of:
a) Better Customer Insights
b) Competitive Advantage
c) Data Cleaning
d) Cost Reduction

Q13. Which is a major challenge of Big Data?
a) Better decision-making
b) Privacy and Security Concerns
c) Innovation
d) Improved productivity

Q14. Which legislation mentioned in the chapter protects personal data?
a) GDPR
b) RTE Act
c) RTI Act
d) IT Rules 2000

Q15. High infrastructure and storage costs are referred to as:
a) Data Quality Issues
b) Cost and Resource Intensiveness
c) Variety
d) Velocity

Q16. The original Big Data framework consists of:
a) 2Vs
b) 3Vs
c) 5Vs
d) 6Vs

Q17. Which of the following is NOT part of the original 3Vs?
a) Volume
b) Velocity
c) Variety
d) Value

Q18. Volume refers to:
a) Data accuracy
b) Amount of data
c) Speed of data
d) Business value

Q19. Velocity refers to:
a) Storage capacity
b) Speed of data generation and processing
c) Different formats
d) Data quality

Q20. Variety refers to:
a) Trustworthiness
b) Different data formats
c) Processing speed
d) Storage cost

Q21. Which characteristic represents data accuracy and reliability?
a) Value
b) Variability
c) Veracity
d) Volume

Q22. Which characteristic measures the usefulness of data for business?
a) Value
b) Velocity
c) Variety
d) Veracity

Q23. Variability refers to:
a) Amount of data
b) Changes and inconsistencies in data streams
c) Storage capacity
d) Database size

Q24. The complete framework discussed in the chapter includes:
a) 4Vs
b) 5Vs
c) 6Vs
d) 7Vs

Q25. Which OTT platform is used as a case study in the chapter?
a) Netflix
b) Prime Video
c) OnDemandDrama
d) Disney+ Hotstar

Q26. Big Data Analytics is the process of:
a) Printing reports
b) Discovering meaningful patterns from data
c) Creating databases
d) Compressing files

Q27. Which type of analytics predicts future outcomes?
a) Descriptive
b) Diagnostic
c) Predictive
d) Prescriptive

Q28. Which type of analytics recommends the best action?
a) Descriptive
b) Diagnostic
c) Predictive
d) Prescriptive

Q29. Moore’s Law contributed to Big Data Analytics by:
a) Reducing storage
b) Increasing computing power
c) Eliminating cloud computing
d) Decreasing internet usage

Q30. Smartphones and tablets mainly contributed through:
a) Cloud Computing
b) Mobile Computing
c) Blockchain
d) Robotics

Q31. Facebook and Pinterest represent which trend?
a) Cloud Computing
b) Social Networking
c) IoT
d) Quantum Computing

Q32. Cloud Computing allows users to:
a) Store data only locally
b) Access computing resources over the Internet
c) Replace databases
d) Eliminate servers

Q33. Which is the first step of Big Data Analytics?
a) Analyze Data
b) Gather Data
c) Clean Data
d) Process Data

Q34. Which processing method analyzes large datasets periodically?
a) Stream Processing
b) Batch Processing
c) Manual Processing
d) Static Processing

Q35. Which processing method minimizes delay between data collection and analysis?
a) Batch Processing
b) Stream Processing
c) Offline Processing
d) Cold Processing

Q36. Data cleaning is mainly performed to:
a) Increase storage cost
b) Improve data quality
c) Slow processing
d) Compress files

Q37. The final step in Big Data Analytics is:
a) Gather Data
b) Clean Data
c) Analyze Data
d) Process Data

Q38. Which software is used in the chapter to demonstrate Big Data Analytics?
a) Tableau
b) Orange Data Mining
c) Python IDLE
d) NetBeans

Q39. Which widget is used to import a dataset into Orange?
a) File
b) Predict
c) Test & Score
d) Data Table

Q40. Which widget is used to normalize numerical values?
a) Impute
b) File
c) Preprocess
d) Predict

Q41. Missing values in Orange are handled using:
a) Predict
b) Impute
c) Heat Map
d) Scatter Plot

Q42. Which model is demonstrated in the chapter?
a) Decision Tree
b) Logistic Regression
c) Naïve Bayes
d) Random Forest

Q43. Which validation technique is recommended?
a) Hold-Out
b) Cross-Validation
c) Random Sampling
d) Leave-One-Out

Q44. Which widget evaluates the performance of a model?
a) Predict
b) Test and Score
c) File
d) Data Table

Q45. A data stream is:
a) Stored historical data
b) Continuous real-time flow of data
c) Printed records
d) Archived database

Q46. Stream mining differs from traditional data mining because it:
a) Stores all data before analysis
b) Processes data as it arrives
c) Uses only structured data
d) Requires offline processing

Q47. A sudden increase in searches for “Election Results” is an example of:
a) Batch Processing
b) Stream Mining
c) Compression
d) Encryption

Q48. Which future trend enables instant business decisions?
a) Batch Analytics
b) Real-Time Analytics
c) Offline Analytics
d) Manual Analytics

Q49. Which technology is expected to revolutionize Big Data through enormous computational power?
a) Blockchain
b) Quantum Computing
c) IoT
d) Edge Computing

Q50. Which statement best summarizes the purpose of Big Data Analytics?
a) To reduce database size
b) To extract meaningful insights for better decision-making
c) To eliminate data collection
d) To replace relational databases completely