#54 Data Mesh Evaluation and Implementation Insights - Interview w/ Steven Nooijen and Guillermo Sánchez

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 hereGoDataDriven Data Mesh Webinar: https://godatadriven.com/topic/webinar-data-mesh-9-feb-2022-thanks/GoDataDriven Self-Service Whitepaper (info-gated): https://godatadriven.com/topic/data-democratization-whitepaper/Steven's LinkedIn: https://www.linkedin.com/in/stevennooijen/Guillermo's LinkedIn: https://www.linkedin.com/in/guillermo-s%C3%A1nchez-dionis/In this episode, Scott interviewed two people from the European data consultancy GoDataDriven - Steven Nooijen, Head of Strategy, and Guillermo Sánchez, Analytics Engineering Tech Lead. Guillermo started off by talking about how for the last ~3 years, he was seeing the data engineering team as the bottleneck before data mesh came onto the scene. For Steven, they were seeing lots of companies that were building out data platforms, especially data lakes, and then not really getting the promised benefits so data mesh made sense. All agreed data mesh is not right for every company and then mentioned some good signs that an organization should consider data mesh. Guillermo pointed to a lot of the usual suspects: size of company, size of data team, how many data consuming teams do you have, how many data sources do you have, etc. He then gave a specific example: if you have a data analyst in a consuming domain that has to wait more than 1 week for data, there is a bottleneck somewhere. Is it centralization? Not sure but time to investigate and that might be where you start to consider data mesh. Steven gave the example of an even earlier indicator that bottlenecks are occurring: teams start to hire their own data people rather than leverage the central team. Guillermo also pointed to the rise of consuming teams getting direct data access from producing teams instead of going through the data team.Guillermo made a very crucial point: data mesh is really about interfaces. People talk about data...

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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