DBTB INT Ian Lin r
my name is Ian lane and i work at realtor.com and my I'm the lead data visualization designer well I I think yeah it's about networking right so you also need to meet lots of people from different industry so that you know the current training what is the future direction you should go and sometimes you also can see some work from other peoples and maybe you think you can relate that kind of things in your work and keep improve yourself and keep being competitive right this is the nature in Silicon Valley well I think data is kind of the source of knowledge for me so the more knowledge you have you you can do things better right but when you have more and more data although you think you can have more and more knowledge but you still need to have a very concise way to interpret the data in maybe before that you also need to pre-process data to make the data cleaning in and then you can do all those modeling and imputation absolute words so that's a very interesting process it's just something like when you see some new things and you also even though you're not a computer you will also try to collect some data from that new things and you try to interpret those data and you kind of create a profile in your mind about that new things so I think that's a very similar process but we just try to utilize the power of computer to help us to facilitate that process so that's very interesting i think even you will think interesting for that right I think the insight the mains I want to bring to user is data is kind of the things you that the result of your observation so when when you observe something or data can also help you to interpret your option observation and then you can based on that kind of observation to take action so that's the I think for me that's the whole thing about data and today I did the talk i have is introduced how we identify the potential business problems in the real estate online real estate website and then how we solve it in how to how we relate that kind of problem as user experience problems so we can make the product even better for our users I think it's just like what I mentioned is kind of the way you interpret data in how you communicate with other people about your findings in that your data science work right if you just run a very solid modeling and the result maybe it's very significant but if you don't have a very compelling way to sell your point maybe it's maybe your work it will be buried underground forever so so I think that my take is I I try to read the data first and then I try to know how the users will use the data or interpret data and then I know what is the users expectation on the data and then I use it as a connection between the users in data scientists to help data science to think about how they can show their findings in a way that common people can easily understand so I think that's also the philosophy of data visualization you