#260 Driving the Big Picture Forward - More on Northern Trust's Data Mesh Implementation - Interview w/ Jimmy Kozlow
Data Mesh Radio - A podcast by Data as a Product Podcast Network
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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.Jimmy's LinkedIn: https://www.linkedin.com/in/jimmy-kozlow-02863513/In this episode, Scott interviewed Jimmy Kozlow, Data Mesh Enablement Lead at Northern Trust. To be clear, he was only representing his own views on the episode.Also, FYI, there were some technical difficulties in this episode where the recording kept shutting down and had to be restarted. So thanks to Jimmy for sticking through and hopefully it isn't too noticeable that Scott had to ask questions without hearing the full answer to the previous question. There is a lot of philosophical discussion in this conversation but tied to very deep implementation experience. It is hard to sum up in full without writing a small novel. Basically, this is one to probably listen to over just reading the notes.Also, Scott came up with a terrible new phrase, asking people to "get out there and be funky."Some key takeaways/thoughts from Jimmy's point of view:Start your mesh implementation with your innovators. Find the people who are excited to try out something new. You want to spend your early time on innovating and learning, not constantly driving buy-in. Find good initial partners!It's okay to start a bit simplistic - with each domain and on your general implementation - because you better believe there are complexities coming as you scale. This is not going to be simple. But the ability to tackle that complexity effectively is what differentiates data mesh so that unavoidable complexity ends up being where you find lots of incremental value.Data product complexity is often from maintaining...