In a previous article, John gave his two cents on what good design means and how to go about evaluating design choices.
John mentioned in the same article that since Traintracks has a mission to democratize data, it's particularly important to design an interface that's intuitive to novice data explorers, rather than to data experts. And that means making a decision to keep Traintracks' UI design consistent with interfaces that most people are familiar with, instead of with those that only data engineers have encountered before. The video below covers a few things about what inspired Traintracks' UI design.
We found when doing research for Traintracks a few years ago that the typical question could go up to $20,000 dollars for a larger company, because several different teams had to get involved. We found over and over again that the typical waiting time for someone that was not an engineer would be something like two weeks to two months until you get an answer back.
Traintracks is very easy to use because it provides an interface for you that allows you to, in a very intuitive way, interrogate data on your own.
So our company is heavily influenced by the 1984 macintosh. Before it came out, there were literally middle-aged employees within corporations that never touched a computer before. And one day their boss would come up to them and say, “Hey Jeff, here’s something called a computer. You’re gonna use this machine to get your work done. By the way, meet Bob. Bob will help you use your computer.”
We feel that the sea of big data is very similar right now, where instead of going through one person to use your computer, you have to go through an army of data scientists to even take a look at your data.
Just like the 1984 macintosh, where you have an interface so easy to use that anyone can just hop on it and start learning how to use a computer. We want the same thing for TT, where because our design looks like an operating system and a lot of people know how to use simple computers that, if someone starts looking at TrainTracks, they could also start analyzing their data.
We spent a lot of effort building a very intuitive user interface that allows non-technical people to interrogate the data in entirely new ways making it specifically easy to ask ad-hoc questions, one-off questions that would've been too expensive task before.
And if you do have technical expertise and you want to build your own reports and applications on top of this data, the work that we have put into making Traintracks accessible through a single API endpoint makes it incredibly easy to build applications on top of Traintracks as a backend.