What issue may arise from having too few data health checks?

Having too few data health checks can lead to a lack of signal when there is an issue, which is important for maintaining data integrity and quality. Data health checks are essential for monitoring the status and cleanliness of data within an application. If these checks are not frequent or comprehensive enough, potential problems in the data, such as inaccuracies, inconsistencies, or missing values, may go unnoticed. This means that users might not be adequately informed when something is wrong, leading to decisions made on flawed or unreliable data.

The absence of sufficient checks can create a situation where issues accumulate, resulting in larger problems that could disrupt operations or lead to misguided insights. Therefore, maintaining a proper frequency and coverage of data health checks is crucial for ensuring that any data issues are detected and addressed promptly, thus preserving the overall reliability of the data being used.