1. What makes Hadoop suitable for large-scale data processing?
Hadoop distributes storage and computation across clusters, ensuring scalability, cost efficiency, and fault tolerance.
2. Why is R widely used in statistical and research analysis?
R offers extensive libraries for regression, clustering, forecasting, and visualization, supporting deep analytical work.
3. Can Hadoop and R be used together in enterprise systems?
Yes, Hadoop manages massive datasets while R performs advanced statistical analysis on refined data outputs.
4. Which industries benefit most from Hadoop and R expertise?
Finance, healthcare, retail, telecom, and cloud services use these tools for analytics and operational efficiency.
5. Does Hadoop require expensive hardware infrastructure?
No, Hadoop runs on clusters of ordinary computers, reducing costs while maintaining reliability and performance.