#139 Reflecting on Learnings from Glovo's Early Data Mesh Journey - Interview w/ Javier Granda and Pablo Giner Abad

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. You can download their Data Mesh for Dummies e-book (info gated) here.Glovo's meetup group: https://www.meetup.com/glovo-tech-talks/Javo's LinkedIn: https://www.linkedin.com/in/javiergrandag/Javo's Twitter: @JavierGrandaG / https://twitter.com/JavierGrandaGPablo's LinkedIn: https://www.linkedin.com/in/pabloginerabad/In this episode, Scott interviewed Pablo Giner Abad, Global Director of Data and Javier "Javo" Granda, Senior Data Manager at Glovo.From here forward in this write-up, P&J will refer to Javo and Pablo rather than trying to specifically call out who said which part.Some key takeaways/thoughts from P&J's point of view:It's okay to not fit the exact or complete picture of data mesh in your early journey. Focus on what matters to your org and implementation and focus on learning over trying to be perfect. Iteration is possible and not too costly with data mesh. That's sort of one of the main points of data mesh.When selecting your first use case, look for high value and low dependencies. The less cross-team coordination work needed to actually get to an initial end data product that has value, the better. And buy-in is much easier if the producers are one of the consumers too :)When starting out, really look at how thin of a slice you can get away with for your MVP. Be prepared to make some hard compromises. Make them with your eyes open. It's tech debt but taken on consciously.Focus on solving your problems of...

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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