Enterprises use Hadoop in data-science applications that improve operational efficiency, grow revenues or reduce risk. Many commercial, open source or internally developed data-science applications have to tackle a lot of semi-structured, unstructured or raw data. Common use cases include log analysis, data mining, machine learning and image processing.
Organizations benefit from Hadoop’s combination of storage and processing in each data node spread across a cluster of cost-effective commodity hardware. Hadoop’s lack of fixed-schema works particularly well for answering ad-hoc queries and exploratory “what if” scenarios.
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