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Which data processing paradigm is best suited for real-time analytics on streaming data?
- Batch Processing
- Stream Processing
- ETL Pipeline
- Data Warehousing
Answer: Stream Processing
Stream Processing (Apache Kafka, Flink, Spark Streaming) processes data in real-time as it arrives, enabling instant insights for fraud detection, IoT monitoring, and live dashboards. Batch processing handles historical data; ETL transforms data for storage; data warehousing supports analytical queries. Critical for modern data architecture questions.