How Do You Deal With Time Zones in Time Series Graphs?
analytics, datetime, google-analytics, time-series, timezone
Solution
First of all, you should recognize that there a lot more than 24 time zones. In order to accurately take into account how people actually use time worldwide, you should be using IANA time zones, of which there are over 500. See also Wikipedia and the timezone tag wiki.
If you are dealing with individual points (discreet timestamps), then you can certainly convert from UTC to any time zone you wish, on the fly as you render your graph. You just need to also keep in mind that the range of data you query will also need to be translated to that time zone.
But if you are talking about aggregating data by the "day" of a specific time zone, then there is no magic bullet. You will need to decide ahead of time which time zones you want to support and calculate each one separately. When you do this, recognize that it's not just the view that's changing. Since the day boundaries are different for each time zone, then the data for each time zone could potentially have very different daily totals.
You should also be aware that not every day has 24 hours. If the day happens to be the date of a daylight saving time transition, it could have 23, 23.5, 24.5, or 25 hours. This could potentially affect how you draw your graph.
One approach you might consider is to be time zone ignorant in your aggregations, rather than using UTC or any specific time zone. Of course this depends heavily on the context of your data, but it is appropriate in certain circumstances. For example, on an invoice, you might care less about the specific timestamps, and more about which calendar date the invoice was assigned to. In that case, once a date is assigned, you would just aggregate on that date. Even if the company operates over multiple time zones, you wouldn't care about that in aggregate.
As far as some clever design that abstracts this from the user, I'm afraid I haven't seen much. The only two choices you really have are timezone-adjusted aggregations (UTC or otherwise), and time zone ignorant aggregations for calendar-date contexts.
Problem
I imagined there would be more literature on this, but I'm having trouble finding any. I have a lot of non-algebraically-aggregatable time series data (that is to say, points for which no function exists that I could use to aggregate them to a higher granularity-- stuff like unique active users, unique contributors, etc... where knowing the amount I had every minute of some hour does not tell me how many I had total during the hour). Currently, I'm just storing and presenting all of this data in UTC. The problem is that many of my clients find this confusing-- understandably so. Because the data is non-algebraically-aggregatable, there's no way to get from UTC data for 1 day midnight- midnight to, say, PST data from midnight to midnight. Recalculation would need to be done from raw data. So: - Recalculation from raw data is prohibitively expensive for some complicated analytics graphs - We could store all data for all time zones, but this would increase the amount of data we store x24. All of that said, how do other people deal with this issue? Here's how Google Analytics does it, but this seems insufficient for my use case because I know if I open the multiple timezone can of worms, clients will ask for more than one. This will also take a lot of work that doesn't seem worth the effort as just adding timezone support won't be extremely noticeable or a huge win. What I'm really hoping for is some clever design solution that just presents the UTC data in some intuitive enough way that it's no longer confusing for people in other timezones. Has anyone dealt with similar problems and come upon a solution I'm missing?