How does big data mining differ from traditional data mining?

Big data mining handles distributed, large-scale, and streaming datasets, unlike traditional centralized mining.

Traditional data mining assumes data fits in memory and is processed on a single machine. Big data mining uses distributed frameworks like Hadoop and Spark, processes streaming data, and focuses on scalability, fault tolerance, and real-time analytics. It introduces challenges in consistency, latency, and system design.