Before starting the maintenance process for a data pipeline in maintenance mode, what should you define first?

Defining the pipeline's data scope and delivery expectations before entering maintenance mode is crucial because it establishes a clear understanding of what data the pipeline will handle and the timeline for data delivery. This information is vital for ensuring that all stakeholders are aligned on what to expect during maintenance. It provides parameters that will guide your decisions during maintenance, such as prioritizing certain data flows or assessing the impact of any changes made.

Knowing the data scope helps identify which datasets are critical and what the quality expectations are, facilitating targeted maintenance efforts. Setting delivery expectations clarifies how and when the data will be available to users, which is essential for maintaining operational continuity and minimizing disruptions.

In contrast, while user access permissions, maintenance costs, and technical architecture of upstream systems are important aspects to address in the broader context of managing a data pipeline, they do not directly inform the immediate goals and actions required for a successful maintenance process. Therefore, establishing the data scope and delivery expectations serves as the foundational step that guides all subsequent maintenance activities.