#236 Driving Buy-in For Decomposing the Monolith; and Then Actually Doing It - Interview w/ Brenda Contreras

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. 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. You can download their Data Mesh for Dummies e-book (info gated) here.Brenda's LinkedIn: https://www.linkedin.com/in/brenda-contreras-9649a47/In this episode, Scott interviewed Brenda Contreras, VP of Engineering and Architecture at Self Financial.Some key takeaways/thoughts from Brenda's point of view:"Iterate small and sell your solutions on a practical level."It's kind of funny how often people in tech try to skip the communication. If you really align on communication and understanding, your business partners are far more likely to empower you to drive business value for them through engineering and data work.?Controversial?: As an engineering/data leader, don't dictate: set the vision, explain the vision to business partners, but try to let your technical team leverage patterns that will work for them instead of only your favorite way. Similarly, make sure your team understands which aspects of target outcomes drive value and why. They might have an approach you didn't expect but if they aren't focused on the key aspects of the outcome, even amazing feats of engineering won't create value if it's not tied to business needs.Fail fast is very important to doing microservices right. How can we learn to adopt it in data and AI? "We need we need to be … able to experiment more, we need to be more flexible" to really drive to business value quicker and easier.Before you start to decompose anything, it's crucial to understand what you already have. That can sound a bit obvious but if you start trying to do the work before understanding the 'before' picture, getting to a good 'after' picture is going to be very...

Om Podcasten

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