Data Mesh in Practice - How Zalando organises its data (in German)

In the challenge of democratising data and its use across an enterprise, the data lake paradigm is often seen as the more scalable successor to the more curated data warehouse approach. Unfortunately, however, if responsibilities are not clear, a centralised data lake can quickly degenerate into a data swamp that adds little value. That is where a Data Mesh can help unlock business value. In this webinar, Max Schultze (Zalando) and Arif Wider (ThoughtWorks) demonstrate how they are moving from a centralised data lake to a distributed data mesh architecture and working towards making the creation of true data products a matter of minutes. Zalando, Europe's leading online platform for fashion, organises its data beyond the data lake paradigm. They realised early on that data accessibility and availability on a large scale can only be guaranteed if primary responsibility lies with those who generate the data and have the appropriate domain knowledge, while centralised responsibility is limited to governance and metadata provisioning. Such a decentralised approach with domain boundaries in focus has recently been described by the data mesh paradigm. Here, so-called data products are put in the foreground, where data is not only made available, but also promises are made regarding data quality and responsibility.