#233 Panel: A Head Data Architect's View of Data Mesh - Led by Khanh Chau w/ Balvinder Khurana, Yushin Son, and Carlos Saona

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.#233 Panel: A Head Data Architect's View of Data Mesh - Led by Khanh Chau w/ Balvinder Khurana, Yushin Son, and Carlos SaonaKhanh's LinkedIn: https://www.linkedin.com/in/khanhnchau/Balvinder's LinkedIn: https://www.linkedin.com/in/balvinder-khurana/Yushin's LinkedIn: https://www.linkedin.com/in/yushin-son-30362b1/Carlos' LinkedIn: https://www.linkedin.com/in/carlos-saona-vazquez/In this episode, guest host Khanh Chau, Director of Cloud Data Architecture at Grainger (guest of episode #44) facilitated a discussion with Balvinder Khurana, Technical Principal and Global Data Community Lead at Thoughtworks (guest of episode #135), Carlos Saona, Chief Architect at eDreams ODIGEO (guest of episode #150), and Yushin Son, Chief Architect of Data Platform & Data Products Engineering at JPMorgan Chase. As per usual, all guests were only reflecting their own views.The topic for this panel was an architect's view of data mesh, especially from an architecture lead standpoint. There are many challenges architects face in data mesh, managing the micro level minutiae, down to the data product output and input port decisions but balance that with crucial high-level decisions. Balancing the near-term and long-term vision and roadmap/North Star. Scott note: I wanted to share my takeaways rather than trying to reflect the nuance of the panelists' views...

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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