#119 Cautionary Learnings From a Startup Doing Data Mesh: Orfium's Journey to Decentralized Data Success - Interview w/ Argyris Argyrou and Konstantinos Siaterlis

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.Argyris Argyrou's LinkedIn: https://www.linkedin.com/in/argyrisargyrou/Konstantinos "Kostas" Siaterlis' LinkedIn: https://www.linkedin.com/in/siaterliskonstantinos/In this episode, Scott interviewed Argyris Argyrou, Head of Data, and Konstantinos "Kostas" Siaterlis, Director of Big Data at Orfium. There is a ton of useful information on anti-patterns, what is going well now, advice, etc. in this one.From here forward in this write-up, A&K will refer to Argyris and Kostas rather than trying to specifically call out who said which part in most cases.Some key takeaways/thoughts from A&K's points of view:On a data mesh journey: "It's not a sprint, it's a marathon." Pace yourself. It's okay to go at your own pace, don't worry about what other people are doing with data mesh, do what's right for you.Really focusing on the why and showing people results was a far better driver to buy-in and participation than any amount of selling about data mesh as a practice. Calling it data mesh when trying to explain it to people outside the data team didn't go well either...Orfium's "Data Doctor" approach - a low friction and low pressure office hours for a general staff data engineer - has really helped people help with data challenges and in spreading good data practices but without the "Doctor" becoming a bottleneck.The Data Doctor's role is to answer questions and provide guidance but not do the work for people. Then, take what was discussed and the best practice and document it for others to learn from - providing good leverage for scaling best data practices.In a smaller company like Orfium (~250 people), it's hard to justify a lot of full-time heads to implement data mesh. And trying to treat a data mesh implementation like a side-project also creates issues. There isn't a great answer here on exactly what to do except possibly take things slower than most startups are used to. Your data will still be waiting for you a few months later.If you are having difficulty driving broad buy-in, showing people what data mesh can do in action...