#102 Share Data by Default and Other Stories/Advice from Leboncoin's Data Mesh Journey So Far - Interview w/ Stéphanie Bergamo and Simon Maurin

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); George Trujillo's contact info: email (george.trujillo@datastax.com) and https://www.linkedin.com/in/georgetrujillo/ (LinkedIn) Transcript for this episode (https://docs.google.com/document/d/1ls5QawrOffb3VGIfZCmPYHG0v729Ye7Gu7oKRaOYi8c/edit (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 Stéphanie Bergamo and Simon Maurin of Leboncoin. Stéphanie is a Lead Data Engineer and Simon is a Lead Architect at Leboncoin. From here on, S&S will refer to Stéphanie and Simon. Some key takeaways/thoughts from Stéphanie and Simon's point of view: "Bet on curious people", "just have people talk to each other", and "lower the cognitive costs of using the tooling" - if you can do that, you'll raise your chance of success with your data mesh implementation. Leboncoin requires teams to share information on the enterprise service bus that might not be directly useful to the originating domain on the operational plane. They are using a similar approach with data for data mesh - sharing information that might not be useful directly to the originating domain by default. Leboncoin presses teams to get data requests to other teams early so they can prioritize it. There isn't an expectation of producing new data very quickly after a new request, which is probably a healthy approach to data work/collaboration. Embedding