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Data is a lot like water; it often needs to be refined as it travels between a source and its final destination. That’s where data pipelines come in – they merge, filter, and summarize raw data, providing the end user with a clean product to analyze. Luv Aggarwal, a Data Solution Engineer at IBM, explains how several processes often embedded within data pipelines – like ETL, replication, virtualization, machine learning, and batch processing – help generate actionable business intelligence.
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