#230 Getting Real About Data Product Management in Data Mesh - Interview w/ Frannie Helforoush

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. You can download their Data Mesh for Dummies e-book (info gated) here.Frannie's LinkedIn: https://www.linkedin.com/in/frannie-farnaz-h-a7a11014/Post on the Product Trio concept by Teresa Torres: https://www.producttalk.org/2021/05/product-trio/In this episode, Scott interviewed Frannie Helforoush, Technical Product Manager/Data Product Manager at RBC Global Asset Management. To be clear, she was only representing her own views on the episode.Some key takeaways/thoughts from Frannie's point of view:There is a difference between the product mindset and creating/maintaining data products but both are very important to exchanging value through data. We should be looking to apply the product mindset to all aspects of our data work, not just how it applies to data products specifically.To do data product management well, you should look to software product management practices and recontextualize those to data. Many map well but some don't. It's not a copy paste, think through what should be applied to data differently.The data product manager needs to serve as the bridge between data producers and consumers, making sure consumer requirements are satisfied much like with a software product manager where they are the bridge between software engineering and software users.If product management is the intersection of business, tech, and user experience (UX), how should we think about that for data product management? Tech and business are easy but there isn't a user interface (UI) so think of UX in terms of data fluency, access, and documentation.Relatedly, documentation around data products is more important than...

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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