The Boss Mare of the Data Nerd Herd | Joe Reis
The Artists of Data Science
Reverse L T Versus T L T
Reverse e t is a term used to describe the process of putting data back into source systems. The gy who developed this come over at a high touch, i think he came up with it as a gy. I got a lot of comments on that, and people took issue more that i was basly cooting a sandwich to describe a data turn - which i'm not apologetic about. All data thing should be named after sandwiches, as would be my edict. Andigo s a good sandwich too.
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Joe is a business-minded data nerd who’s worked in the data industry for 20 years.
In his two decades as a practitioner he’s worked on the full gamut of data tasks from statistical modeling, forecasting, machine learning, data engineering, data architecture, and almost everything else in between.
He’s taken all that experience and started his own venture and is currently the CEO of Ternary data.
Watch the video of this episode: https://youtu.be/6jGmXBaTJkI
Memorable Quotes from the episode:
[00:42:09] "...My other piece of advice, which is, do you lose money for the firm? I'll be understanding. If you lose a shred of reputation, I will be ruthless. Let's talk with me. Right. Reputation is everything. As he also says, it takes a lifetime to build a reputation. It takes 15 minutes to destroy it. So when we started our business, I thought it was interesting. We didn't really care about the money. We cared about reputation and cared about doing great work, meeting great people and just, I think developing good relationships. I always optimizing for reputation. I think we thought if we could build that pile of reputational capital, the money would follow. The reverse is rarely true, though. In the short term, you can build as much money as you can, but you can destroy your reputation. And then who's going to want to do business with you?"
Highlights of the show:
[00:01:11] Guest Introduction
[00:03:34] Joe, where did you grow up and what was it like there?
[00:05:22] What were you like as a high school kid? What did you think your future would look like?
[00:06:46] When you'd make the move over to Salt Lake City? Was that when you started working? Did you go to school there?
[00:09:08] What was it like kind of when you first started out and what drew you to this kind of field (data science)?
[00:14:02] Where is the science in data science? Is there any science in data science? Is it scientism?
[00:26:10] How did you guys link up and decide to start ternary data and can we even get the story behind the companies name as well?
[00:27:23] What are some problems that you just see as a consultant pop up over and over?
[00:34:06] Do engineers add value and how should we think about a return on investment for the work that they do?
[00:41:23] Talk to us about your blog post about the concept of reputational capital.
[00:43:04] Do you have any tips for people who are just early in their data science career. In their first job as a data scientist, how can they accrue some of this 'reputational capital'?
[00:45:56] How reading science fiction has made you a better technologist? What science fiction has done for you, has it made you a better technologist?
[00:47:44] What would you say is the one sci-fi work that's had the biggest influence on you as a technologist?
[00:51:04-00:51:17] You've got such a dope setup here. What's all this about? The keyboards? You got turntables, you got multiple keyboards. Are you making your music. Do you got any undercover Spotify?
[00:52:59] It's 100 years in the future. What do you want to be remembered for?
Random Round
[00:54:02] When do you think the first video to hit to 1 trillion views on YouTube will happen? When will that happen and what will that video be about?
[00:55:33] What song do you have on repeat?
[00:55:53] What are you currently reading?
[00:59:19] What's kind of your process when you're reading?
[01:03:12] What talent would you show off in a talent show?
[01:03:39] What do you mean by organizational behaviour?
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