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.