#79 A Data Success Secret Recipe: Comfort with Ambiguity and Change Management - Interview w/ Vincent Koc

https://www.patreon.com/datameshradio (Data Mesh Radio Patreon) - get access to interviews well before they are released Episode list and links to all available episode transcripts (most interviews from #32 on) https://docs.google.com/spreadsheets/d/1ZmCIinVgIm0xjIVFpL9jMtCiOlBQ7LbvLmtmb0FKcQc/edit?usp=sharing (here) Provided as a free resource by DataStax https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio (AstraDB) Transcript for this episode (https://docs.google.com/document/d/17Fl1bLCmzqh-mlozccziGnWMslsPOfvJdejhgp3FIlw/edit?usp=sharing (link)) provided by Starburst. See their Data Mesh Summit recordings https://www.starburst.io/learn/events-webinars/datanova-on-demand/?datameshradio (here) and their great data mesh resource center https://www.starburst.io/info/distributed-data-mesh-resource-center/?datameshradio (here) In this episode, Scott interviewed Vincent Koc, Head of Data at the merchant platform company hipages. To start with some big takeaways from Vincent: ⦁ If you aren't comfortable with an agile mindset and ambiguity, bleeding edge probably isn't for you - and that's okay! ⦁ You and your organization need to be comfortable with failing, learning, and then iterating ⦁ To get data mesh - or really any big change initiative in data - right you should focus on change management much more than you probably think ⦁ It ends up being the secret sauce or crucial lacking factor much more often than the tech ⦁ Think problem-specific, not technology specific ⦁ It's easy to over-engineer the problem - technologists want to technology ⦁ In general, consistency is key to achieving widespread success in data ⦁ One domain having a major success won't lead to broader org-wide success if you don't look to leverage reusability factors to make consistency across other domains easy - a bunch of great but non-consistent solutions doesn't add up to a valuable whole picture For Vincent, every organization considering data mesh should ask if it is really the correct approach for them. D