#27 Four Key Pillars to Driving Data Mesh Buy-in and Other Insights - Interview w/ Angelo Martelli

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.Angelo's LinkedIn: https://www.linkedin.com/in/angelomartelli/In this episode, Scott interviews Angelo Martelli, Group Leader of Data Services at logistics company Vanderlande. Angelo laid out his framework for driving data mesh buy-in internally at Vanderlande which helped them take the idea from a small group to a company-wide initiative:Start with proving there is a problem that you are trying to solve - if everything is functioning well, why focus your efforts on that area instead of trying to fix another? Your proof should be as fact-based as possible, e.g. how long does it take to make a change to your data warehouse. Focus on proving that your incremental investments are driving sub-linear returns. Other areas to look to prove problems: how many people are involved in a change to your data warehouse, percent of time spent on regression testing versus development, mean time to resolution of challenges, etc. Once you have some proof, you need to work towards understanding the problem you are trying to solve. It's not "deploying a data mesh", it's scaling the organization to be agile relative to data and be able to make more (and better) data-informed decisions. Next, you need to understand your organization. Who are the right people that can help you? How does your organization work relative to culture and process? Which domains are struggling and how? Tie the implementation goals to the actual business challenges.Then, you need to demystify data mesh, make it easy to understand for people not well versed in data - what are we actually trying to accomplish and why? Last, make it concrete / prove it out. Make a few data products, make a simple platform for folks to use. Angelo then recommends that once you have momentum, sharing a very clear vision is crucial. Not just sharing in a document but actually having conversations to really make sure the context and vision is understood. Data mesh is about collaboration, you must work together so it is imperative to make expectations very clear. Similar to Abhi Sivasailam, Angelo also stressed the importance of the domain data model and abstracting that away from the application model(s). The business model is what matters for data. All of that and so much more. Also, Angelo gives a shout out to the usefulness of the Data Mesh Learning community. 😎Data Mesh Radio is hosted by Scott Hirleman. If you want to connect with Scott, reach out to him on LinkedIn: https://www.linkedin.com/in/scotthirleman/If you want to learn more and/or join the Data Mesh Learning Community, see here:

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Interviews with data mesh practitioners, deep dives/how-tos, anti-patterns, panels, chats (not debates) with skeptics, "mesh musings", and so much more. Host Scott Hirleman (founder of the Data Mesh Learning Community) shares his learnings - and those of the broader data community - from over a year of deep diving into data mesh. Each episode contains a BLUF - bottom line, up front - so you can quickly absorb a few key takeaways and also decide if an episode will be useful to you - nothing worse than listening for 20+ minutes before figuring out if a podcast episode is going to be interesting and/or incremental ;) Hoping to provide quality transcripts in the future - if you want to help, please reach out! Data Mesh Radio is also looking for guests to share their experience with data mesh! Even if that experience is 'I am confused, let's chat about' some specific topic. Yes, that could be you! You can check out our guest and feedback FAQ, including how to submit your name to be a guest and how to submit feedback - including anonymously if you want - here: https://docs.google.com/document/d/1dDdb1mEhmcYqx3xYAvPuM1FZMuGiCszyY9x8X250KuQ/edit?usp=sharing Data Mesh Radio is committed to diversity and inclusion. This includes in our guests and guest hosts. If you are part of a minoritized group, please see this as an open invitation to being a guest, so please hit the link above. If you are looking for additional useful information on data mesh, we recommend the community resources from Data Mesh Learning. All are vendor independent. https://datameshlearning.com/community/ You should also follow Zhamak Dehghani (founder of the data mesh concept); she posts a lot of great things on LinkedIn and has a wonderful data mesh book through O'Reilly. Plus, she's just a nice person: https://www.linkedin.com/in/zhamak-dehghani/detail/recent-activity/shares/ Data Mesh Radio is provided as a free community resource by DataStax. If you need a database that is easy to scale - read: serverless - but also easy to develop for - many APIs including gRPC, REST, JSON, GraphQL, etc. all of which are OSS under the Stargate project - check out DataStax's AstraDB service :) Built on Apache Cassandra, AstraDB is very performant and oh yeah, is also multi-region/multi-cloud so you can focus on scaling your company, not your database. There's a free forever tier for poking around/home projects and you can also use code DAAP500 for a $500 free credit (apply under payment options): https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio