#123 Reflecting on Multiple Data Mesh Implementations: Iterating Your Way to Success - Interview w/ Sunny Jaisinghani and Simon Massey
Data Mesh Radio - A podcast by Data as a Product Podcast Network
Categories:
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.Get in touch with Simon and Sunny: [email protected] webinar (info gated) Sunny and Simon did on data mesh: https://events.esynergy.co.uk/data-mesh-experimentation-to-industrialisation-on-demandSimon's LinkedIn: https://www.linkedin.com/in/simon-massey-82718a3/Sunny's LinkedIn: https://www.linkedin.com/in/sunnysjaisinghani/In this episode, Scott interviewed Sunny Jaisinghani and Simon Massey who are both Principal Consultants at the consulting company esynergy. They have been involved in multiple data mesh implementations including at a large bank. This episode could also have been titled: Aligning Incentives, Reducing Friction, and Continuous Improvement/Value Delivery but it doesn't roll off the tongue very well.From here forward in this write-up, S&S will refer to Simon and Sunny rather than trying to specifically call out who said which part as that leads to confusion.Some key takeaways/thoughts from S&S's points of view:We are all still early in our learnings about how to do data mesh well. There is still a ton left to learn. Which is why people should share what they are learning more broadly. Helping others will help you.Data mesh, whether it's your overall implementation, your platform, your data products, your ways of working, etc. is all about evolution, incremental improvement, iteration, etc. You...