How do you automate and orchestrate your data pipeline workflows and schedules?
Data pipelines are essential for processing and transforming large volumes of data from various sources and delivering them to different destinations. However, building and managing data pipelines can be challenging, especially when you need to handle complex dependencies, errors, retries, logging, monitoring, and scheduling. That's why you need to automate and orchestrate your data pipeline workflows and schedules, so you can save time, reduce errors, and ensure consistency and reliability. In this article, we'll show you how to do that using some common tools and best practices.
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