What is an important consideration when scheduling data synchronization?

The importance of scheduling data synchronization before any dataflows are run lies in the need for ensuring that the data being processed is the most current and accurate. When data synchronization occurs first, it lays the groundwork for subsequent dataflows, guaranteeing that all analyses and operations are based on the latest data. This is crucial for maintaining the integrity and reliability of any insights derived from the data.

If data synchronization were to happen after the dataflows, the analyses would utilize outdated information, which could lead to misguided conclusions or decisions drawn from inaccurate datasets. This foundational step ensures the entire data pipeline functions efficiently and with up-to-date information, which is particularly important in environments where data changes frequently.

Scheduling synchronization weekly or performing it manually might optimize specific operational contexts, but they do not speak directly to the procedural necessity of having the most recent data beforehand for effective analytics processes.