In Big Data Analytics, what is the main function of the MapReduce programming model?

MapReduce is a programming model designed to process large-scale data by distributing computations across multiple nodes in a cluster. The model works by breaking down tasks into the "Map" phase, where data is distributed and processed in parallel, followed by the "Reduce" phase, which aggregates the results. This distributed computing model is highly scalable and fault-tolerant. Store large datasets : This is handled by HDFS or other distributed file systems, not MapReduce. Clean data : Data cleaning can be part of MapReduce jobs but is not the core function of the model. Visualize large-scale data : Data visualization is not part of the MapReduce model; other tools like Tableau or Hadoop are used. Perform batch processing : MapReduce can perform batch processing, but its main advantage is distributed computation.