#88 Data Engineering and Data Engineers' Future in Data Mesh - Interview w/ Joe Reis

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.Links:Joe's LinkedIn: https://www.linkedin.com/in/josephreis/Ternary Data Website: https://www.ternarydata.com/Monday Morning Data Chat: https://anchor.fm/ternary-dataJoe and Matthew Housley's interview with Zhamak Dehghani: https://www.linkedin.com/video/event/urn:li:ugcPost:6915063013410582528/Joe's upcoming book, "Fundamentals of Data Engineering": https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/In this episode, Scott interviewed Joe Reis, CEO/Co-Founder of data consultancy Ternary Data, Co-Host of the Monday Morning Data Chat, and author of the upcoming book Fundamentals of Data Engineering.Some key points or takeaways specifically from Joe's point of view (not necessarily those of the podcast):Find quick, high-value wins. Too often people focus on the big wins and those become overly complicated and end up in failure.Most software engineers don't understand data well enough to be data product developers in data mesh, at least yet.Data mesh is a polarizing topic. And that makes sense as it is pushing boundaries. Many hope it can come to fruition but it is a bit of a utopian view.The future of data engineering is to move past managing pipelines to much higher-value work.Speed to achieving wins with data - with a clear return on investment and trust - is the first thing you should focus on. Get this right and you can have the "luxury" of building great data products.Joe started by discussing the kind of nebulous area within software engineering and data that data engineering has always played - sit between the source systems and the data output, converting the data in the source systems into something consumable for data users. Previously, that was mostly about making...

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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