CSD33503-Chap10-Data Mining Trends Quiz

What best defines the concept of data mining trends in the context of modern data science?

• The outdated methods used for static data analysis

• The evolving patterns, techniques, and technologies shaping the future of data mining

• The decline of data analytics due to privacy concerns

• The temporary strategies applied to clean small datasets

Why is it crucial for data scientists to stay updated with emerging trends in data mining?

• To maintain obsolete systems for longer periods

• To focus only on historical data and ignore future patterns

• To remain competitive, adopt innovative tools, and improve data-driven decision-making

• To reduce the number of data sources being used

Which of the following is NOT a current trend in data mining?

• Cloud-based data analytics

• Real-time and stream data mining

• Manual data entry optimization

• Integration of AI and ML in predictive analytics

Which trend allows data mining applications to scale efficiently, handling large, complex datasets across multiple systems?

• Manual data validation

• Distributed systems and cloud computing

• Spreadsheet-based analysis

• Local server-only computations

How have Artificial Intelligence (AI) and Machine Learning (ML) transformed data mining practices?

• By replacing all predictive analytics models with manual techniques

• By enhancing predictive analytics and enabling adaptive decision-making models

• By reducing the need for automation

• By limiting data mining to numerical data only

Which of the following challenges is associated with mining big data, and how is it addressed by parallel processing frameworks like Hadoop and Spark?

• Limited dataset size, addressed by spreadsheets

• Complex data volumes, processed efficiently using distributed frameworks

• Data privacy, solved by cloud backups

• Outdated algorithms, addressed by printed reports

Which of the following are considered research frontiers in data mining? (Choose the correct pair)

• Email management and spreadsheet formatting

• Deep learning for big data and privacy-preserving data mining

• Barcode scanning and cloud billing

• Data archiving and compact disk storage

Real-time and stream data mining are especially valuable in which of these industries? (Choose two)

• Online banking and industrial monitoring

• Textbook publishing and historical archiving

• Print journalism and postal services

• Static report generation and document filing

Why are privacy-preserving data mining (PPDM) techniques becoming increasingly important today?

• They make all data public for marketing

• They improve personal data sharing without controls

• They protect sensitive data while allowing useful analysis in regulated environments

• They eliminate the need for data security systems

What is a key opportunity associated with mining data from IoT-generated streams?

• Increasing paperwork

• Real-time operational insights for smart cities, homes, and industries

• Making decisions based on old records

• Limiting data access to a single user