#263 Panel: Applying Site Reliability Engineering Practices to Data - Led by Emily Gorcenski w/ Amy Tobey and Alex Hidalgo

Please Rate and Review us on your podcast app of choice!Get involved with Data Mesh Understanding's free community roundtables and introductions: https://landing.datameshunderstanding.com/If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see hereEpisode list and links to all available episode transcripts here.Provided as a free resource by Data Mesh Understanding. Get in touch with Scott on LinkedIn if you want to chat data mesh.Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here. You can download their Data Mesh for Dummies e-book (info gated) here.Emily's LinkedIn: https://www.linkedin.com/in/emily-gorcenski-0a3830200/Amy's LinkedIn: https://www.linkedin.com/in/amytobey/Alex's LinkedIn: https://www.linkedin.com/in/alex-hidalgo-6823971b7/Alex's Book Implementing Service Level Objectives: https://www.alex-hidalgo.com/the-slo-bookIn this episode, guest host Emily Gorcenski, Head of Data and AI for Thoughtworks Europe (guest of episode #72) facilitated a discussion with Amy Tobey, Senior Principal Engineer at Equinix and Alex Hidalgo, Principal Reliability Advocate at Nobl9. As per usual, all guests were only reflecting their own views.The topic for this panel was applying reliability engineering practices to data. This is different than engineering for data reliability which is focused on data quality specifically. The overall concept is taking what we've learned from reliability engineering across disciplines but mostly in software, especially SRE/site reliability engineering, and bringing those learnings to data to make data - especially data production and serving - more reliable and scalable. Scott note: this is probably one of the most frustrating topics in data for me because it feels like it's basic foundational work yet most organizations aren't tackling this well yet if at all really. The best starting...