https://netlify.zoom.us/rec/share/v2at679tFm30oyAQT-Z3UIypauIJbU7C9s8ujAZUUVHUboNao1YZfWsp8vaqv8Ds.lbQ_SU5eRnl9zLCc?startTime=1649777566000 (Passcode: 1j+&qA)

WEBVTT

1 00:00:00.000 --> 00:00:01.890 Simon Knott: date and all recording.

2 00:00:04.290 --> 00:00:18.720 Simon Knott: So things a lot files anymore just interview Just to give you some general context I have done, like half a year of what we call a bachelor's project we work with some research of some industry partners and do some research.

3 00:00:19.200 --> 00:00:27.960 Simon Knott: And our case we work with mobility data, there was like live extract from some German smartphones and.

4 00:00:29.340 --> 00:00:34.800 Simon Knott: That data chain frequently and that company did not like that that we partnered with.

5 00:00:36.600 --> 00:00:47.850 Simon Knott: did not have good workflows around it like what happened frequently was day saying oh oh data changed phones are sending in a row different patterns and that happened, four months ago, all the analysis is broken.

6 00:00:50.250 --> 00:00:50.850 Simon Knott: and

7 00:00:51.300 --> 00:00:52.710 Laurie Voss: This all sounds very familiar.

8 00:00:54.690 --> 00:00:56.370 Simon Knott: And that that's what I was hoping for.

9 00:00:57.450 --> 00:01:13.530 Simon Knott: The so I, I have the assumption that this is called a thing that's special to that company and it happens at other companies to do so i'm doing like some research interviews across different industries different companies, research, like data engineering all those.

10 00:01:14.280 --> 00:01:16.170 Simon Knott: different kinds of applications.

11 00:01:16.470 --> 00:01:32.970 Simon Knott: To find out what's the problem what things exist to solve it, and how can I like what could be another time to solving a problem and now i'm very much like understanding the trying to understand the actual like.

12 00:01:34.650 --> 00:01:44.850 Simon Knott: What would be great is, if you can skip the question, what does your company do, but could you like in a club sentences tell me what you do that before.

13 00:01:46.740 --> 00:01:50.760 Laurie Voss: So I am a data evangelist so.

14 00:01:50.790 --> 00:01:57.120 Laurie Voss: My role is split between internal and external fixing things half of my role is.

15 00:01:58.260 --> 00:02:06.060 Laurie Voss: Showing findings internally and the other half the role is supposed to be giving conference talks and other sorts of external facing things like blog posts and White Papers and stuff.

16 00:02:07.110 --> 00:02:18.540 Laurie Voss: But, in both cases, what i'm doing is i'm plugging myself into all of magnifies internal data and all of the external industry data that I can at the same time.

17 00:02:19.110 --> 00:02:32.370 Laurie Voss: and looking for things that are actionable there sometimes it'll be like we need to pay more attention to this product, or we need to start paying attention to these kinds of users, when it's external facing it's often stuff like.