Please note:
On this site, there is only displayed the English speaking sessions of the TDWI München digital. You can find all conference sessions, including the German speaking ones, here.
The times given in the conference program of TDWI München digital correspond to Central European Time (CET).
By clicking on "EVENT MERKEN" within the lecture descriptions you can arrange your own schedule. You can view your schedule at any time using the icon in the upper right corner.
Thema: Data Mesh
- Montag
20.06. - Dienstag
21.06.
Künstliche Intelligenz ist schon längst dem Pionierzeitalter entwachsen. Doch um mit dem Einsatz von KI einen echten Mehrwert für das Unternehmen zu schaffen, kommt es auf die qualitativ hochwertige Bereitstellung von Daten an. Hier kommt ML Engineering ins Spiel - ein Konzept zur Bewältigung der hohen Komplexität von Daten bei der Entwicklung von KI-Systemen. Im Vortrag wird eine ML Engineering Roadmap vorgestellt, mit der dieses häufig unterschätzte und doch so kritische Konzept erfolgreich…
As the data mesh paradigm takes the industry by storm, the conversation deep dives into the architecture, neglecting the socio-organizational element. Data driven organizations must invest not only in infrastructure but also data organization and culture.
Target Audience: Executive, senior business managers
Prerequisites: None
Level: Basic
In order to succeed in creating a data driven enterprise it is clear that choosing the right data architecture is now critical. This session explores the evolution of data and analytics architecture and looks at what is needed to shorten time to value and create a data driven enterprise. It looks at the pros and cons of data lake, lakehouse and data mesh architectures and asks: Is there a best approach? Is a lot more than this needed to succeed?
Target Audience: Data architects, CDOs, CAOs,…
SWICA historically runs a data warehouse built by a centralized team and in parallel, multiple isolated solutions for domain specific analyses, which afford high maintenance and an extensive effort to stay compliant.
Modernizing our analytical environment, we are building a collaborative platform on MS Azure, utilizing the Data Mesh paradigms of data domain and data product.
We aim to deliver a managed data marketplace for all data domains to provide their data products on a modern platform with…