#40 Getting Data-as-a-Product Right and Other Learnings From Adevinta's Data Mesh Journey - Interview w/ Xavier Gumara Rigol

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 (info gated)Xavier's Twitter: @xgumara / https://twitter.com/xgumaraXavier's LinkedIn: https://www.linkedin.com/in/xgumara/Adevinta meetup presentation: https://www.youtube.com/watch?v=av6cT_r4orQXavier's Medium Articles:https://medium.com/adevinta-tech-blog/building-a-data-mesh-to-support-an-ecosystem-of-data-products-at-adevinta-4c057d06824dhttps://medium.com/adevinta-tech-blog/treating-data-as-a-product-at-adevinta-c1dce5d394c5https://towardsdatascience.com/data-as-a-product-vs-data-products-what-are-the-differences-b43ddbb0f123Scott interviewed Xavier Gumara Rigol who has been helping lead Adevinta's data mesh implementation as Area Manager for Experimentation and Analytics Enablement. The discussed the data as a product concept and learnings from Adevinta's journey thus far. Xavi has put out some great articles and did a Data Mesh Learning meetup that are linked below.One key aspect to data as a product is to understand the need for data product evolution, both relative to maturity and to what is consumed. This is a common theme in many data mesh conversations as historically, data consumption has resisted evolution and change. Consumers need to really understand that the business is evolving so what they consume will too. If you manage data products well, it won't be a sudden change but if we are trying to share insights into a domain, those insights will change. When thinking about data product maturity, it's totally okay to start by thinking of a data product as a single table or view. Xavi also mentioned some pitfalls to forced data product evolution - e.g. getting it wrong as changes can be quite costly to backfill. Adding new attributes is easy but computing something for 3 to 6 months in hindsight can cost a

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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