A data pipeline serves as a processing engine that transports raw data from database sources to data warehouses for further analytics. Highly efficient and modern data pipelines are just as critical for the success of big data analytics since they enable to swiftly extract information from its source, convert it into a usable format, and load it into destination systems where data is analyzed for insightful decisions in real-time. This drastically cuts down the time from data capture to analysis to insight.
Rigid and slow, legacy data pipelines, in their turn, feed information in batches. This results in high data latency, forcing data scientists to simplify data or use a limited data set for analysis, and hence allows gaining only superficial insights providing little value.