10 data pipeline challenges your engineers will have to solve

The challenges of building or buying a reliable and well-functioning data pipeline include reverse engineering the underlying data model, handling schema drift, automating the process, enabling users to build new data assets, dealing with incremental updates, ensuring idempotence, parallelizing operations, pipelining and buffering, scaling and extensibility, and managing security and PID. These challenges are complex and require careful consideration of technical problems and potential solutions.

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