#93 Empower to the People: Data Collaboration and Observability at Enterprise Scale - Interview w/ Jay Sen
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Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/Please Rate and Review us on your podcast app of choice!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 / Scott Hirleman. 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.Jay's LinkedIn: https://www.linkedin.com/in/jaysen2/Posts by Jay:Next-Gen Data Movement Platform at PayPal: https://medium.com/paypal-tech/next-gen-data-movement-platform-at-paypal-100f70a7a6bHow PayPal Moves Secure and Encrypted Data Across Security Zones: https://medium.com/paypal-tech/how-paypal-moves-secure-and-encrypted-data-across-security-zones-10010c1788ceThe Evolution of Data-Movement Systems: https://jaysen99.medium.com/evolution-of-data-movement-f12614d6e9deIn this episode, Scott interviewed Jay Sen, Data Platforms & Domain Expert/Builder and OSS Committer. While Jay currently works at PayPal, he was only representing his own view points.Some key takeaways/thoughts from Jay's view:When you get to a certain scale, any central team should focus on, as Jay said, "Empower people, don't try do their jobs." That's how you build towards scale and maintain flexibility - your centralized team likely won't become a bottleneck if they aren't making decisions on behalf of other teams.To actually empower other teams, dig into the actual business need and work backwards to a solution that can solve that. If there is a solution already in place that isn't working any more, look to find ways to augment that rather than trying to replace or reinvent the wheel.Self-service is a slippery slope - it often solves the immediate problem of time to market but also creates next level challenges. A big issue is that when you remove the friction to data access, you are throwing challenge of finding right data on consumers plate. Data contracts are great when everybody aligns on a single contract and there are enough tools to support the contracts. But they also create a proliferation of data to enforce the contracts required by multiple consumers - thus,...