One of the benefits of pulling all your data together is that you can overlay data sets on top of one another for further insight. I only noticed this today but Pacific Gas & Electric’s Usage History section is great example. Here’s my gas bill over the past 24 months available to me when I login to the pge.com. The bars represent the total monthly gas usage and the shaded area is the average temperature for the month.
Laid out this way, it makes total sense that I would see a spike for January two years ago and a lower peak that extended for two months last year. The “degree days” (calculated as a varience from 65 F) map almost perfectly. If it were out of whack, I’d wonder but a quick check here and it looks like I’m on target.
Imagine the power of shared data sets like these. Mint, the online money management service, also provides a shared view of aggregate spending so you can compare what you spend to others around you. Using Mint’s Spending Trends feature, you can see how much (or little) I spend on Hair Care compared to my fellow San Francisco Mint users.
I had no idea someone could spend $419 on Hair in a month but there you have it (and that’s the average). Just for giggles I checked some of the other cities and it looks like someone in the Bay Area is throwing things out of whack – NYC only spends $152 and even LA is a mere $297. Either hair dressers are really ripping off people here or someone has a really expensive hair habit.
What other examples are there of such shared data sets. I’ve heard of sites that compare salary levels and another that lets you put in the MPG you get on your make and model of car. 23andMe is doing this across personal genetics. Any others?