What is the advantage of creating a new pipeline for shared datasets in Foundry?

Creating a new pipeline for shared datasets in Foundry primarily allows for independent scheduling, which is the key advantage of such an approach. By establishing a dedicated pipeline, teams can schedule data processing tasks according to their specific needs and timelines, enhancing flexibility in managing data workflows. This means that different teams or applications can rely on the same underlying data without being affected by each other's processing schedules.

Independent scheduling also enables teams to optimize their data workflows, ensuring that data is available when it's needed without conflicts from other processes that might rely on the same datasets. This level of independence helps maintain efficiency and responsiveness in data operations, particularly in environments where multiple projects or data consumers are concurrently utilizing shared datasets.

While streamlining the data retrieval process, facilitating easier version control, and potentially complicating the overall architecture are considerations in data engineering, these are secondary to the significant operational advantage of independent scheduling provided by a new pipeline dedicated to shared datasets.