If you are like me, you look at a lot of data. I look at data in spreadsheets, I look at data on P&L statements, I look at term sheets, I look at systems data — a lot of systems data. I find the best way to look at data is to visualize it because it is the fastest way to get data into the amazing pattern matcher that is the human brain.
The human brain is quite good at saying “this is abnormal” and can usually even articulate why. This curve has a periodicity, that one a monotonic behavior, another is simply always flat… then they “change.” When we say “this visualization looks wrong,” we are almost always onto something real in the numbers. I’ll give you a simple visual example:
While there is obviously something starting at 8pm, we are only left with another question: “is it out of the ordinary?” It doesn’t look like that today, and it doesn’t appear to resemble the day before. What about last week? Let’s start the graph one week earlier:
This tells us a lot. It looks like we have a very similar event last week at this time. With most analysis tools, you stop here (or you hover with you mouse and try to correlate start/end times and magnitude to better understand how these two events resemble each other).
With Circonus, we don’t leave it here. Instead, we provide tools to help compare time separated events using our data overlay feature. We can take our original two-day view and overlay the data from last week right on top of (or in this case underneath).
Just two clicks and we’ve got a one-week offset data overlay and the visualization lends a little insight into what is going on. We can see the start times are identical, but the event from this week ends about 30 minutes before the one from last week — largely the same though.
Again, we find that visuals help. Understanding how these graph differ even when they are right on top of each other can be a bit challenging. Never fear! We’ve added help in the legend.
The legend takes on some new features when data overlays are in use. You now get a very clear, side-by-side read-out of the data in the graph including percentage differences. Additionally, the arrows that say “you’re higher than you were last week” become more saturated (redder) as the different in the data increases and fade to light grey if the two values are more similar. This makes it simple to quickly understand how current performance really compares to past performance. So, the interesting part of this graph is actually the subsequent spike of inbound traffic this is up 95% over last week. That’s something to look into.