Transcript: DBTB INT Katherine Ahern r

my name is Catherine a Hearn and I managed the visualization and analytics Department at clear story data there are two things one is it gave me a deadline to accomplish some things that I promised for the talk which was very helpful for me professionally and the other is that I came early and I'm getting to hear some real industry leaders just amazing talks particularly on machine learning and I've been interested in predictive analytics and UX on large data sets for a while so seeing both how young the industry is is very validating because when clear story handles some very challenging projects you sort of sometimes I feel like it the answer should be obvious but it's actually a pretty young industry so we're all working on pretty new technologies and using new metaphors using new techniques I've always thought data was cool and exciting um you know when I started grad school we were talking about the data explosion and I was in 2004 and it was amazing that you could have terabytes of data that's just psychotically large was like more than in history and there was this hockey stick curve to just sheer quantity and now my my own dad is talking about needing a bigger computer because he needs a terabyte to store his vacation photos just the the scale is really I didn't think it would get bigger but it has by many many multiples I know it's yeah I mean there was the perception that things couldn't get faster that there was gonna be some sort of plateau but that was a decade ago you know 15 years ago pay attention to user intention clarity of communication availability of workflows and whether that will yield correct analytics results because they're there ways to mislead people that can be subtle and but true so ways to sort of bring in tension ality to user selection of data I'm speaking specifically of aggregation levels of aggregation and granularity and so ways of bringing user attention to that but not overwhelming a user with workflows or selection opportunities that are irrelevant because that is a tough balance in developing a analytics product uh well I you should learn d 3 and then come work at clear story if you want to become great if you want to become good enough you can um work for other companies