Partitions in Data Pipelines

A partitioned data asset is a way of modeling data that lies between a single monolithic data asset and a set of distinct data assets. Partitioning helps data engineers and ML engineers organize data and computations, making data pipelines more performant and cost-efficient by operating on subsets of data instead of all of it at once. Data orchestrators need to understand partitions to effectively run data pipelines, as they help answer questions like "what needs to be done?" and "what did I do?". Without an understanding of partitions, data orchestration can lead to uncertainty, less trustworthy data, and painful debugging. Dagster is a data orchestrator that strives to fully model the relationship between computation and data, including partitioned data assets and pipelines, making it well-suited for modeling partitions.

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