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Open Source vs. Proprietary DataOps

Core DataOps concepts are making their way into data engineering teams and, from there, into the broader enterprise. Data engineers are retooling how they create data products, and much of this work revolves around creating data pipelines.

DataOps pipelines offer the kind of observability that traditional data integration and ETL processes don’t or can’t. They allow you to continuously integrate and test new data sources and deliver data in streaming or batch contexts with higher levels of quality and reliability than traditional, siloed approaches. They can also support machine learning efforts by preparing data for training, testing and deployment.

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