#304 Getting Your Data Mesh Journey Moving Forward - Interview w/ Chris Ford and Arne Lap玫nin
Data Mesh Radio - Un p贸dcast de 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.Transcript for this episode (link) provided by Starburst. You can download their Data Products for Dummies e-book (info-gated) here and their Data Mesh for Dummies e-book (info gated) here.Arne's LinkedIn: https://www.linkedin.com/in/arnelaponin/Chris' LinkedIn: https://www.linkedin.com/in/ctford/Foundations of Data Mesh O'Reilly Course: https://www.oreilly.com/videos/foundations-of-data/0636920971191/Data Mesh Accelerate workshop article: https://martinfowler.com/articles/data-mesh-accelerate-workshop.htmlIn this episode, Scott interviewed Arne Lap玫nin, Data Engineer and Chris Ford, Technology Director, both at Thoughtworks.From here forward in this write-up, I am combining Chris and Arne's points of view rather than trying to specifically call out who said which part.Some key takeaways/thoughts from Arne and Chris' point of view:Before you start a data mesh journey, you need an idea of what you want to achieve, a bet you are making on what will drive value. It doesn't have to be all-encompassing but doing data mesh can't be the point, it's an approach for delivering on the point 馃槄Relatedly, there should be a business aspiration for doing data mesh rather than simply a change to the way of doing data aspiration. What does doing data better mean for your organization? What does a "data mesh nirvana" look like for the organization? Work backwards from that to figure where to head with your journey.A common early data mesh anti-pattern is trying to skip both ownership and data as a product. There are existing data assets that leverage spaghetti code and some just rename them to data products and pretend that's moved the needle."A data product is a data set + love." The real difference between a data product and a data set is that true ownership and care.?Controversial?: Another common mesh anti-pattern is trying to get too specific with definitions or...