#127 A Quest for Readiness: The Importance of Capacity to Change in Data - Interview w/ Winfried Etzel

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.Winfried's LinkedIn: https://www.linkedin.com/in/winfried-adalbert-etzel/MetaDAMA podcast (episodes in both English and Norwegian): https://podcasts.apple.com/us/podcast/metadama-en-helhetlig-podcast-om-data-management-i-norden/id1572639573In this episode, Scott interviewed Winfried Etzel, Information Strategy Consultant at Bouvet, Board member of DAMA Norway, and host of the MetaDAMA podcast. Some key takeaways/thoughts from Winfried's point of view:Transformation teams - a team that helps domains to transform and upskill by embedding in the domain for a time - is an exciting pattern for data mesh.Transformation teams can collect information more easily and find patterns as they are closely collaborating with more domains.Think of transformation teams like a personal trainer - they help you get in shape so you learn what exercises to do and how but then you can work on your own. And you can engage them again if you need more help.How can we give guidance and enable change at the same time - the transformation teams shouldn't do the work for the domains but need to work with them. Can we go broad in the organization if we only have a limited number of transformation teams? Do we need to be in that much of a hurry where that's an issue?There's definitely some vendor washing going on around data mesh. It's often difficult to determine what is new and what they've recycled to sound new.In data, we should look to take many learning from software engineering but also other...