Understanding Data Foundations | Loris Marini

Watch the video of this episode: https://youtu.be/wvkxi-Et29M
Find Loris Marini online: https://www.linkedin.com/in/lorismarini/
https://www.discoveringdata.com

Support the show: https://www.buymeacoffee.com/datascienceharp

Memorable Quotes from the show:

[00:33:01] "We all matter, we are all part of this and we need one another. I can't do that a science well, if the data is not reliable, if it's not trusted, if it's not connected to the business via metadata by a data management program that touches anyone. And so it's really a mind, a change of of mindset from. You can add value as a team in isolation to, well, not really. Data is the common denominator to everything we do, whether we like it or not. Everything we do generates Data."

Highlights of the Show:

[00:01:27] Guest Introduction.

[00:03:01] Where did you grow up and what was it like there?

[00:05:13] What the heck is quantum photonics and how did you get into that?

[00:08:51] How did you go from awesome, crazy physics stuff into Data science?

[00:12:41] Talk to us about your experience of hardcore physics and research and how did that experience lead you into the Data project?

[00:14:58] What did that look like when you were venturing out as the first data scientist?

[00:17:57] Data architecture. Talk to us about that transition. What was that transition like? What made you be like, "Oh my God, I need to put the Data science down and pick up the Data architect stuff"

[00:21:11] What is the difference between Data engineer and the data architect?

[00:24:47] What do you think a data scientist at a minimum should know about Data architecture and the role that Data architect plays?

[00:35:27] You're talking about the difference between data, information, knowledge and strategy. What's the difference between these? How does data, information or knowledge play into a strategy?

[00:40:44-00:40:46] What's the name of that podcast by Brian O'Neill?

[00:53:03] I love creating machine learning models and then you're trying to do stuff and then you realize that your hands are tied because there's no infrastructure in place; there's no desire or nobody cares about your fancy algorithms and anything like that. How can we start making a culture happen for success?

[00:58:04] Talk about this latter of Data needs that goes from data integration, data access and data transformation kind of walk us through that process and then talk to us about why transformation that part is so hard.

[01:02:03] It's one hundred years in the future. What do you want to be remembered for?

[01:04:00] What do you think is the most mysterious aspect of the universe, which you say that this uncertainty principle is that? Or is there a different thing that is more mysterious than that to you?

[01:05:02] When do you think the first video to hit one trillion views on YouTube will happen and what will that video be about?

[01:05:33] Who do people tell you that you look like?

[01:06:10] What are you currently reading?

[01:07:17] What song do you currently have on repeat?

[01:08:02] What's the last book you gave up on and stopped reading?

[01:08:45] What fictional place would you most like to go to?

[01:09:21] What languages do you speak?

[01:09:25] If you were a vegetable, what vegetable would you be?

Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh
Register for Sunday Sessions here: http://bit.ly/comet-ml-oh
Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark

The Artists of Data Science Social links:
YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience
Instagram: https://www.instagram.com/datascienceharp
Facebook https://facebook.com/TheArtistsOfDataScience
Twitter: https://twitter.com/datascienceharp