This infographic outlines key data engineering principles for effective data movement. Incremental updates are preferred over full syncs, as they only process changes using change data capture, saving time, compute, and bandwidth. Idempotence ensures repeat operations yield the same results, preventing duplicates and easing recovery from failures. Schema drift handling is critical for maintaining reliable pipelines when source structures change, with live updating replicating source models accurately at the destination. To optimize network performance, pipelines should use algorithmic improvements, parallelization, and pipelining, which processes data in sequential yet overlapping stages for efficiency.

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