Which of the following is considered a pitfall of data health check setups?

Setting up too many checks can indeed be a pitfall of data health check setups. When there are excessive checks in place, it can lead to a number of issues. For starters, managing and monitoring these checks becomes cumbersome, making it harder for developers and data engineers to focus on the most critical aspects of data health. An overwhelming number of checks can also create noise, where the volume of alerts and reports obscures more important signals that need immediate attention. This can result in alert fatigue, where users become desensitized to notifications, potentially causing them to miss important issues.

In contrast, the other options describe practices that can enhance data health checks rather than detract from them. Ignoring user feedback can certainly be detrimental, but it does not directly correlate with the operational challenges posed by excessive checks. Adding automated datasets and conducting regular maintenance are typically beneficial practices that help improve the effectiveness and reliability of data health checks. Thus, while those options may have their own challenges, they do not represent the same stark pitfalls associated with an overabundance of checks.