#81 Finding Useful and Repeatable Patterns for Data - Interview w/ Shane Gibson

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.Shane's LinkedIn: https://www.linkedin.com/in/shagility/Shane's Twitter: @shagility / https://twitter.com/shagilityAgileData.io website: https://agiledata.io/AgileData Way of Working: https://wow.agiledata.io/Shane's Podcasts: https://agiledata.io/podcasts/In this episode, Scott interviewed Shane Gibson, CPO/Co-Founder of AgileData.io and Agile Data Coach. A few takeaways from Shane to start:- Agile methodology is about finding patterns that might work, trying them out and deciding to iterate or toss out the pattern. It's going to be hard to directly apply software engineering patterns to data but we should look for inspiration there and then tweak them.- Any time you look at a pattern you might want to adopt or evaluate if a pattern is working for you, ask yourself: will this/does this empower the team to work more effectively?- Applying patterns is a bit of a squishy business. Get comfortable that you won't be able to exactly measure if something is working. But also have an end goal in mind for adopting a pattern - what are you trying to achieve and is this pattern likely to help you achieve that?- Share your patterns to not only help others but to get feedback and maybe ideas to iterate your pattern further.Shane's last 8 years have been about taking Agile practices and patterns and applying them to data as an Agile Data Coach. And those patterns required a lot of tweaks to make them work for data. A big learning from that work is that when applying patterns in Agile in general, and specifically in data, each organization - even each team - needs to test and tweak/iterate on patterns. And that patterns can start valuable, lose value, and then become valuable again. Shane gave the example of daily standups drive collaboration as a forcing function but then lose value when that collaboration becomes a standard team practice. If there is 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