#270 Sustainable Data Transformation to Drive Towards Data Mesh - RBI's Journey So Far - Interview w/ Stefan Zima

Please Rate and Review us on your podcast app of choice!Get involved with Data Mesh Understanding's free community roundtables and introductions: https://landing.datameshunderstanding.com/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.Transcript for this episode (link) provided by Starburst. You can download their Data Products for Dummies e-book (info-gated) here and their Data Mesh for Dummies e-book (info gated) here.Stefan's LinkedIn: https://www.linkedin.com/in/stefan-zima-650229b7/In this episode, Scott interviewed Stefan Zima, Data Transformation Lead at RBI (Raiffeisen Bank International AG). To be clear, he was only representing his own views on the episode.Some key takeaways/thoughts from Stefan's point of view:No one has data mesh all figured out. Go talk to each other. But also don't be ashamed that you are running into challenges. So is everyone else. Data mesh implementers also need to share more of the anti-patterns they are finding.Agile transformation really focuses a lot on communication and transparency. Both are very crucial to really any successful transformation initiative. Humans struggle with uncertainty and change so giving them a lot of information especially about the why prevents unnecessary pushback. Relatedly, there are many things we can take from Agile transformation practices to apply to data/data mesh transformation. It's not a copy/paste but there's still much that is very relevant with some tweaks.Many organizations are still focusing on technology-led transformation, whether data or digital in general. You must also change the mindset and organizational approaches if you want to be successful.In banking, the rise of fintechs (financial technology companies) has made it clear that being nimble and quickly acting on data is crucial. Being data driven is required to remain competitive.Data mesh can mean far less friction in getting to serving use cases. Instead of fighting against the data protection office, they are involved from the start. That time to market is especially crucial in banking now.If you can, look to make your data sharing policies and approaches generic enough to only create friction when there truly is something different that should be examined further.If you really want to be 'data-driven', if you really want to be a data company, you have to find and address the friction points in your data processes. Stop trying to simply get better at processes that...