What defines unstable measurements?

Unstable measurements are typically characterized by how data is aggregated and presented. When the aggregation settings are set to 'Not Auto' and the granularity is 'None', it means that the system is not automatically processing the data into a structured format that allows for reliable measurement over time. This can lead to inconsistencies and fluctuations in the data, making it unstable. Without automatic aggregation and with a lack of granularity, the resulting measurements may vary widely, making them less dependable for analysis and decision-making.

In contrast, other options either suggest configurations that enhance the stability of data or do not directly relate to instability. For example, if aggregation settings are 'Auto', this indicates that the system processes the data automatically and likely applies consistent aggregation rules, which contributes to stable measurements. Similarly, setting a measurement with the LIFETIME aggregation function typically summarizes data over a longer period, promoting consistency and reducing fluctuations. Lastly, having a granularity defined as 'Not Empty' suggests that some structure is retained in the data, which aids in developing stable measurements rather than contributing to their instability.