Parallel loading is a data loading strategy that involves loading multiple datasets or partitions simultaneously to improve the efficiency and speed of the data ingestion process. This technique allows for faster data processing by utilizing multiple threads or processes, which can significantly reduce overall load times. By leveraging parallelism, organizations can enhance their data integration processes and better handle large volumes of data.
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