#76 A Skeptic's View of Data Mesh and Learning Your Data Product ABCs - Interview w/ Tim Gasper

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.Tim's Twitter: @TimGasper / https://twitter.com/TimGasperCatalog & Cocktails page: https://data.world/podcasts/Data.world blog content:Do You Know Your Data Product ABCs? https://data.world/blog/data-product-abcs/The Role of a Data Catalog in Data Mesh https://data.world/blog/data-catalog-data-mesh/In this episode, Scott interviewed Tim Gasper, VP of Product at data.world and the co-host of the Catalog & Cocktails podcast. They covered two main topics - 1) the skeptic's view of data mesh and 2) Tim's/the data.world team's "ABCs of Data Products" framework.Skeptics have a few main pushbacks on data mesh in Tim's view. Tim listed the top 6 that he sees and then discussed them with Scott.#1: Data mesh isn't for every organization depending on size, number of domains, data/problem space complexity, etc. Tim said this. Zhamak has said this. Most data mesh advocates/fans say this regularly. This is one of the myths of data mesh - that it's designed for everyone. Don't go to a decentralized data setup if you don't need to. Tim made the very good point that we need more conversations and better guidance on what to measure if centralization of your data team and processes is your actual challenge.#2: Tooling doesn't exist - yet? - to make it easy for domains to easily take over data ownership. A big conceptual myth of data mesh is that it has to solve every data problem, even the most difficult, right out of the gate. Tim mentioned that your team needs to really think about self-service being about empowerment, not necessarily a single big red easy button. And your implementation will evolve - it MUST evolve. It's not easy yet and if your team isn't prepared to roll up their sleeves, it's okay to wait to implement.#3: There shouldn't be anyone who "owns" the data. Tim made a really good point here on accountability to sharing your data versus the...

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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