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Deep in the heart of data // Carl Steinbach // MLOps Coffee Sessions #22

Deep in the heart of data // Carl Steinbach // MLOps Coffee Sessions #22

FromMLOps.community


Deep in the heart of data // Carl Steinbach // MLOps Coffee Sessions #22

FromMLOps.community

ratings:
Length:
56 minutes
Released:
Dec 18, 2020
Format:
Podcast episode

Description

Coffee Sessions #22 with Carl Steinbach of LinkedIn, Deep in the Heart of Data.

//Bio
Carl is a Senior Staff Software Engineer and currently the Tech Lead for LinkedIn's Grid Development Team. He is a contributor to Emerging Architectures for Modern Data Infrastructure

//Other links referenced by Carl:
https://rise.cs.berkeley.edu/wp-content/uploads/2017/03/CIDR17.pdf
https://www.youtube.com/watch?v=-xIai_FvcSk&ab_channel=WePayEngineering
https://softwareengineeringdaily.com/2019/10/23/linkedin-data-platform-with-carl-steinbach/
https://www.slideshare.net/linkedin/carl-steinbach-open-source
https://dreamsongs.com/RiseOfWorseIsBetter.html
https://engineering.linkedin.com/blog/2017/03/a-checkup-with-dr--elephant--one-year-later
https://engineering.linkedin.com/
https://engineering.linkedin.com/blog/2018/11/using-translatable-portable-UDFs
https://a16z.com/2020/10/15/the-emerging-architectures-for-modern-data-infrastructure/

--------------- ✌️Connect With Us ✌️ -------------
Join our slack community: https://go.mlops.community/slack
Follow us on Twitter: @mlopscommunity
Sign up for the next meetup: https://go.mlops.community/register

Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with David on LinkedIn: https://www.linkedin.com/in/aponteanalytics/
Connect with Carl on LinkedIn: https://www.linkedin.com/in/carlsteinbach/

Timestamps:
[00:00] Introduction to Carl Steinbach
[00:44] Carl's background
[04:51] Breakdown of Transpiler
[10:55] Advantages of Decoupling the Execution Layer
[15:25] Differences between UDF (user-defined function) Functions and Views
[18:45] How do you ensure the reproducibility of these Views?
[23:58] Data structure evolution
[27:55] Are Data Lakes and Data Warehouse fundamentally different things or are they on a path towards conversion?
[33:37] It's inevitable that people will start doing machine learning on databases
[36:01] Who gets permission on what, especially when it comes to data and how sensitive things can be?
[41:27] Security aspect of data  
[43:40] Does it require a level of obstruction on top of the data of the file system?
[45:48] Why do we go back and go forward which sets this trend?
Released:
Dec 18, 2020
Format:
Podcast episode

Titles in the series (100)

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.