I thought that these sparklines might be an interesting way to represent data on the IMA Dashboard, and so I’m experimenting by bringing this nugget of wisdom to bear on a chart that I haven’t been very pleased with.

This is the chart that we have on the dashboard to display power readings from our machine room (please note that these charts were all generated on Monday, Sept 21st 2009 and thus do not include the readings for that day). The problem here is that I was trying to show three different things, and none of them ended up being communicated very well. Because I’m trying to show individual measurements along with the total, the scale on the vertical axis diminishes the appearance of trends in the data. It is fairly clear that overall, consumption dropped during this period, and that there appears to be a significant decline in usage by the server components. But it is hard to tell if there is also a trend in the cooling system measurements.

The same story about the overall consumption could be told by this sparkline representation of the previous 28 daily totals:

The maximum value over this period is shown by the dot at 1350 kWh, the minimum value is 1222 kWh, and the latest value (from yesterday) is 1227 kWh. This sparkline includes eight values from last month, and you get same story with more precise information added by a single sentence, all in significantly less space than the original graph… pretty potent stuff.

Applying a sparkline to the server readings, we can see that after the peak at 807 kWh, consumption dropped and is leveling out around the lastest value at 759 kWh. Okay, so that was an attempt at using the sparkline as a word-like sentence element, which is supposed to be one of it’s strong points. It actually works fairly well, even scaled down to font-size, but here’s the sparkline at the native resolution:

The sparkline clearly reflects a drop in consumption a little over a week ago, which is due to the removal of some units from our server rack.

Similarly, we can look at the cooling system readings, which fell from 545 kWh four weeks ago to 457 kWh when we raised the thermostat setting by 3°F, and has been slowly climbing on average since then to 468 kWh – a fact that is more difficult to derive from the original bar chart.

So, it seems that sparklines can be useful for teasing out information about general trends. But, there are a few things to be careful about. For example, each of these sparklines has it’s own vertical scale, so while trends can be compared, the actual differences in consumption cannot. Also, I might look at those bumps in the cooling system sparkline and wonder if those occurred on warmer days. I may then look at the temperature records and see a pattern that appears similar, but without the actual dates and readings I’d be treading on thin ice in forming any conclusions.

So, I think I’ll add the sparkline to my array of tools, but I’m still deciding how to use it’s principles to improve upon our power consumption chart.