Consider running a computationally expensive batch job that runs once an hour. On successful run a data point equal to 1 is recorded, a failed job or lack thereof results in no data being published at all.
The following chart illustrates how presentation of the same data at different temporal granularities may lead to two different conclusions.
The green line represents successful runs with 1-hour granularity, and the red line displays the sum of successful runs in every 8-hour interval.
On the green line the multi-hour gaps between successful runs became invisible when looking at extended periods of time, and occasional stacking up of 2 successful runs in one hour around July 13th does not suggest trouble. But the red line tells a very different story, and clearly suggests that since June 20th the load cannot be met with available capacity. Organic growth?
For more on temporal granularity in monitoring time series data, see this post.