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Every aspect of the financial services industry is undergoing some form of transformation. By leveraging the power of real-time data streaming, financial firms can drive personalized customer experiences, proactively mitigate cyber risk, and drive regulatory compliance.

What is data mesh and why is it gaining rapid traction among data teams?
Join us on February 13 to talk with Michele Goetz, VP, Principal Analyst at Forrester for a deep dive into the business benefits of a data mesh architecture.

In this two-part series, you’ll get an overview of what Kafka is, what it's used for, and the core concepts that enable it to power a highly scalable, available and resilient real-time event streaming platform.

Join Ryan James, Chief Data Officer of Vitality Group, to learn how Vitality Group future-proofed its event-driven microservices with Confluent and AWS

Learn about the new key features in the Confluent Cloud Q1 2023 launch - Centralized Identity Management (OAuth), Enhanced RBAC, Client Quotas and more that enable you to build a secured shared services data streaming platform.

In this session, you’ll learn how to accelerate your digital transformation using real-time data.

Confluent’s Stream Designer is a new visual canvas for rapidly building, testing, and deploying streaming data pipelines powered by Kafka.

Join this webinar to explore the state of data streaming for the Manufacturing Industry in 2023.

This fireside chat will cover Suman’s learnings from implementing 2 critical use cases at Walmart that continue to play a critical role in customer satisfaction: real-time inventory and real-time replenishment.

During the pandemic the Asia Pacific region (APAC) fared relatively well compared to its US and European counterparts. But is the pressure of global inflation and the threat of recession finally catching up?

Learn how Apache Kafka® on Confluent Cloud streams massive data volumes to time series collections via the MongoDB Connector for Apache Kafka®.

Join this webinar to find out how a data mesh can bring much-needed order to a system in both cases, resulting in a more mature, manageable, and evolvable data architecture.