#42 Self-Serve Consumption Means Empowerment, Not Chaos - Interview w/ Ust Oldfield

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.Ust's LinkedIn: https://www.linkedin.com/in/ust-oldfield/Ust's Twitter: @UstDoesTech / https://twitter.com/UstDoesTechIn this episode, Scott interviewed Ust Oldfield, Principal Consultant at Advancing Analytics. They covered the concept of self-serve from a consumer standpoint in data mesh, and some ideas around how to get it right. According to Ust, the overall data and analytics industry is just starting to move from data consumers only consuming what others have prepared towards self-serve data consumption. But, it is important to still provide those prepared reports so 1) people are working from the same info / on the same page and 2) you give people an easy - and maintained - path to important business information.Ust also mentioned one key to getting self-serve right is to not just enable consumers to get to the data they want, they really need to be able to understand what they are seeing so documentation, sample queries, and other similar tactics are very crucial. Consumers also need training on how to use the platform - in general, training for self-serve data consumption is very lacking across the industry right now.How do we share information at scale? Forums? "Show and Tell"? Office hours? Neither Ust nor Scott had great answers just yet. Time will tell.Ust finished with a recommendation for those building out their self-serve platforms for data consumption: spend a lot of time interviewing your data consumers to figure out what will empower them rather than just trying to deliver what you would want. Also, make sure to enable those who just want to consume data as prepared - those who want to be spoon-fed the info, that's fine, allow them to self-select as that is a valid approach to leveraging data.Data Mesh Radio is hosted by Scott Hirleman. If you want to connect with Scott, reach out to him on LinkedIn: https://www.linkedin.com/in/scotthirleman/If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see hereAll music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman):

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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