All About Data Products - Interview with Wannes Rosiers, CTO Golazo Group

In this episode, Scott interviews Wannes Rosiers, CTO at Golazo Group, who previously led DPG Media's data mesh transition. They discussed a lot of different sub-topics around data products in data mesh including: Wannes' framework re his 3 types of data products The importance of a specific purpose for each data product Data product evolution from single purpose to multi-purpose The owner roles/functions related to data products in data mesh How to get moving with an initial data mesh implementation Data product interoperability and global definitions and identifiers Wannes' LinkedIn: https://www.linkedin.com/in/wannes-rosiers/ Wannes' data mesh related content: Meetup presentation: https://www.youtube.com/watch?v=l_5fkpweQwM Domain Driven Design for Data at DPG Media: https://dpgmedia-engineering.medium.com/ddd-data-area-at-dpg-media-f0130e4d9766 A specific run down of data mesh at DPG: https://dpgmedia-engineering.medium.com/data-mesh-at-dpg-media-dfebdd612087 A co-authored post with Snowflake: https://levelup.gitconnected.com/data-mesh-a-self-service-infrastructure-at-dpg-media-with-snowflake-566f108a98db Short video describing DPG's overall data journey, not just data mesh: https://itexecutive.nl/leveraging-the-power-of-data-technology/data-strategy/van-goed-op-weg-zijn-met-data-naar-data-rock-star-in-twee-jaar/ Golazo Careers Page: https://www.golazo.com/jobs/ Data Mesh Radio is hosted by Scott Hirleman. If you want to connect with Scott, reach out to him at community at datameshlearning.com or on LinkedIn: https://www.linkedin.com/in/scotthirleman/ If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here: https://docs.google.com/document/d/1WkXLhSH7mnbjfTChD0uuYeIF5Tj0UBLUP4Jvl20Ym10/edit?usp=sharing All music used this episode created by Lesfm (intro includes slight edits by Scott Hirleman): https://pixabay.com/users/lesfm-22579021/ Data Mesh Radio is brought to you as a community resource by DataStax. Check out their high-scale