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Value proposition of the system is done to specify the need of the project. Once the project is approved, spark programs, also called spark jobs, are written to extract data from the databases and stored on Hadoop clusters. The data is then filtered according to the business needs using spark jobs and then this filtered data is placed on the file system again using spark in a format that can be used by SparkML. Spark speeds up the operation by parallelizing the operations. The data stored ondoi:10.22214/ijraset.2019.6123 fatcat:rv5xc4aixzg2tnidixfoglstoa