Visit Dennis Will's link: https://www.linkedin.com/in/dennis-will-226407168/
Video of the episode: https://youtu.be/FvimZnYhzK0
MEMORABLE QUOTES FROM THE EPISODE
[00:07:10] "I think Python is actually a very good language to get into even as your first language, but you still should be open to what the language offers and what it's offered beyond Python. So I think C is a good starting point, but I think it might actually turn off a lot of people because it is very inherently difficult. Like a lot of concepts that seem like like the way pointers work, that's something that you don't even have to deal with in Python if you don't want to."
[00:12:00] "...usually companies don't want to spend that much money. So that's why you have to think up a solution that is very efficient, very memory efficient and in the end also gets the job done."
[00:13:24] "You have one big cluster which has several workers, and this allows you to process data in parallel. And what I don't like is that it is a very useful to know, but most in most cases, you don't need that. It's very expensive. It's only for a very huge data sets and companies like to use for every single thing. So a lot of the things you can actually do with other services like like serverless functions that are a good example."
[00:25:51] "A very good example that in the previous years has grown and a lot of companies say, we want to do machine learning, we want to do data science, but they don't even know what that means. That's why I think that it's going to get more important because for data science to be able to work properly, you need a good architecture to Data in the right place. And I think only going to get bigger from here."
HIGHLIGHTS OF THE SHOW
[00:00:55] Guest Introduction
[00:02:44] Talk to us about where you grew up and what was it like there?
[00:04:34] What's your comments on Art and Museums in Berlin?
[00:05:11] In high school, what did you think your future would look like?
[00:06:10] What was the language of choice back then?
[00:07:06] Do you think C would be the way to go?
[00:08:10] How did you get interested in Data engineering?
[00:09:32] What are a couple of concepts, maybe two to three concepts that you think would be extremely beneficial for a data scientist to learn about data science so that we can help make each other's lives easier?
[00:12:35] Do you use any frameworks or packages to help you with data engineering? Does anything like that exist that we should probably know about or I?
[00:14:24] There's always new stuff popping up, and you always have to try to keep up on stuff. How do you manage that? New tech comes out that you either hear or read about. What's your process for determining? Is this something I should spend my time?
[00:17:05] How did you find yourself getting into Azure?
[00:18:47] How important do you think being resourceful has been in your career?
[00:20:04] Difference between a Data architect and a Data engineer. So how are these two roles similar? How are they different?
[00:23:24] What are some of the things that you would ask your client so that you can figure out what it is that you need to go do?
[00:27:20] What aspiring Data engineers can do now to help prepare themselves for the future?
[00:30:13] What are some of your favorite misconceptions about what it is that a Data engineer does?
[00:31:30] What can a Data scientists do to make the lives of their Data engineering colleagues easier?
[00:33:09] Do you have any words of encouragement or advice to share with anyone who's afraid to ask questions because they don't want to look stupid?
[00:44:15] Do you have any tips or any ideas on how to work on a Data Engineering project?
[00:46:30] What are some tips you can leave with our audience on how we can be more valuable in our jobs?
[00:48:06] It's 100 years in the future. What do you want to be remembered for?
[00:49:58] Random Round
[00:50:02] When do you think the first video to hit one trillion views on YouTube will hap