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Online Talk

Data Mesh: From Concept to Implementation

A conversation with Confluent featuring Forrester and Raiffeisen Bank International

Available On-demand

While the benefits of a data mesh architecture are clear, what’s not as obvious are the implementation challenges for businesses, especially those working with legacy data pipelines. Building a data mesh the right way requires a modern approach to data pipelines that includes streaming data so you can get the right data to the right teams in the right format at the right time.

Join us on May 17 for a deep dive into the best practices to implement a data mesh architecture.

In this webinar, you’ll hear from:

  • Analyst Michele Goetz on best practices for building a data mesh
  • Kai Waehner, Global Field CTO at Confluent, on the principles for building better data pipelines for a data mesh architecture
  • Thomas Joham, RICE Delivery Manager and Fisnik Bocolli, Product Owner, Event-Driven Architecture Platform and Governance at Raiffeisen Bank International (RBI) on how streaming pipelines helped RBI implement a data mesh across 12 subsidiary banks and architect democratized data access

Bring your questions on May 17 as we talk through this exciting topic from concept to real-life implementation. Join us!

プレゼンター

Guest Speaker Michele Goetz

VP, Principal Analyst, Forrester

Michele Goetz serves enterprise architects, chief data officers, and business analysts trying to navigate the complexities of data while running an insight-driven business. Her research covers artificial intelligence technologies and consultancies, semantic technology, data management strategy, data governance, and data integration.

Kai Waehner

Global Field CTO, Confluent

Thomas Joham

RICE Delivery Manager, Raiffeisen Bank International

Fisnik Bocolli

Product Owner, Event-Driven Architecture Platform and Governance, Raiffeisen Bank International

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その他のリソース

cc demo
kafka microservices
Image-Event-Driven Microservices-01

その他のリソース

cc demo
kafka microservices
microservices-and-apache-kafka