Excited to be presenting alongside @Christof Wenzeritt at Data Dreamland! Main topic is Data Mesh and how to do one. It offers an effective approach for managing large-scale data, but the transition isn't always smooth sailing. Join us when we delve into the challenges of designing ownership structures within a Data Mesh framework. We'll explore how to achieve the optimal balance between technical expertise and organizational design. Let's share our knowledge and navigate the exciting world of Data Mesh together! Get your ticket here: https://scalefr.ee/d7goui

In principal Data Mesh offers a brilliant approach to managing data at scale, decentralizing ownership while maintaining centralized governance. However, that requires a lot of change in the organization and without a clear strategy, Data Mesh can easily lead to anarchy, data silos and many more meetings. I'm very much looking forward to be taking the stage with @Marc Winkelmann at Data Dreamland to dive into this topic with our presentation: "Data Mesh Governance: Taming the Wild West of Distributed Ownership" I hope to see many of you in Hanover! Sign up here if you want to join: https://scalefr.ee/d7goui #DataGovernance #DataManagement #DataDreamland

https://www.rnz.co.nz/news/business/527419/inland-revenue-giving-thousands-of-taxpayers-details-to-social-media-platforms-for-ad-campaigns?fbclid=IwY2xjawFLSwJleHRuA2FlbQIxMAABHfiQoZd2lKNuLPKWDo5IrGSrtYtTKNwWBrS0kfJBtccVTTWP9FPKrjY3zg_aem_jp9YxiznNYVeVO5Oo9wqfA

Relational stages handle structured data with real-time processing and schema validation, while Data Lakes are built for unstructured data, offering flexibility and scalability for large datasets and analytics. Where do you see the biggest differences in how they’re used in your Data Vault setup?

Hi All - I have just joined after completion of Data Vault 2.0 Bootcamp.