The important part to think of is how you create your structure and what type of cycles are interesting to look at. Would it make sense to look at values across weeks, months or quarters and to try to find periods within your data?
Time point vs time interval
When we look at the temporal data it’s also of interest to know if the value is a point or if it represents an interval. In the case of a point the aggregation often doesn’t matter as it’s never used. In the first chart below I have two different temperature fields and I’m just plotting the values as they are. There can only be one maximum and one minimum temperature per day. But in the chart below I have data on an hourly rate and I want to see the average temperature per day. Hence it makes sense to use the average function to get a good representative value.
Now that we know a bit more about time we can also start using time together with mapping. One example of this is the space-time cube which shows a three-dimensional visualization of the data. In this case, I’m going back to one of my favorite visualizations, Charles Minard’s map. In this version we can also see how the army moves not only over land, but also time. Thus we know that Napoleon’s speed getting to Moscow was slower than his retreat, we can also tell the period he stayed in Moscow.
I hope this was educational for you! We have made some great time and date additions to Qlik Sense 3.0 and it gave me inspiration to write this post.