#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...