Data Science Happy Hour 24 | 19MAR2021

Mar 21, 2021

Ask episode

Chapters

Transcript

Episode notes

Vote in the data community content creators awards! http://bit.ly/data-creators-awards

Check it out and don't forget to register for future office hours: http://bit.ly/adsoh

If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70

Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFw_ty92wJoWzoO7WlfaM7iYB8_qjm

[00:03:27] What are examples of times when you think that Data is not an appropriate solution to the problem?

[00:05:08] If one is trying to force Data to solve a business problem where it doesn't belong, then that is not a great approach for any problem solving.

[00:08:53] Data itself shouldn't lead to anything.

[00:16:35] A question around end-to-end data projects, specifically how to approach planning one.

[00:19:28] Thom Ives shares how to think through a project pipeline

[00:23:39] Ben Taylor talks about how to approach a project

[00:24:47] A corporate perspective for planning a project

[00:28:36] Antonio with a mic drop

[00:30:57] Which LinkedIn post would become an NFT in the future?

[00:37:03] What is the biggest pain points in your process, that if you alleviate with a magic wand, would make your life soooo much easier?

[00:38:37] Ben Taylor chimes in with some insight to this question

[00:41:59] Antonio: I think this is all communication. Honestly, ninety five percent of the problems I see are related to the communication rather than technology

[00:47:41] The importance of MLOps and documentation

[00:51:38] As a manager for one silo, you are not understanding the other silo and therefore you're not able to communicate through language barriers.

[00:53:07] Even if I know the answer, I'll still ask those questions so that I can benefit, or maybe somebody else can benefit from it.

[00:56:18] Thom has a conspiracy theory about David Langer

[00:56:51] What do you think is the next wave in data science?

[01:04:52] Data Science is such a broad field, and I don’t know If I am I technical enough

[01:06:13] Santona: I think technical ability is so vague and broad and very context specific

[01:09:01] Mikiko shares some awesome advice

[01:12:22] Greg: And what I can tell you is if you focus on gaining industry knowledge, you will be so comfortable with tackling what needs to be done from the technical side to solve these business problems. So the more business savvy you are, the better you can communicate with business folks, identify their problems, then you can work backwards to figure out you need technical skills that you need to solve them.

[01:13:25] Specialize or generalize?

[01:15:05] What are the things that school can't teach you?

Special Guests: Kate Strachnyi, Kurtis Pykes, Mikiko Bazeley, and Santona Tuli, PhD.