SumUp scales with data mesh built on Confluent

SumUp, a leading fintech company, has transformed its data management strategy by implementing a data mesh architecture on Confluent Cloud. This move has enabled the company to decentralize data access, accelerate innovation, and empower teams to make data-driven decisions.

Faced with the challenge of siloed data and bottlenecks in accessing timely insights, SumUp adopted Confluent Cloud, a fully managed Apache Kafka service. This allowed them to shift from a centralized data management model to a decentralized, self-service approach, aligning with data mesh principles. By empowering individual teams to build and own standardized data streams, SumUp unlocked the potential of previously isolated information, transforming it into reusable data products.

The transition to Confluent Cloud has had a significant impact across various teams within SumUp. For instance, the Global Bank tribe leverages Confluent Cloud to enhance data distribution capabilities between microservices, ensuring real-time updates to merchant accounts. The CRM team now delivers seamless customer experiences by providing real-time information to operational teams. Additionally, the risk data and machine learning platform team has standardized data pipelines, enabling their models to make decisions based on the latest data.

Looking ahead, SumUp plans to extend its data mesh rollout to include multi-region clusters, aligning with its expansion into new markets like the United States and Australia. The company also aims to leverage real-time stream processing and data sharing tools to further empower internal teams and deliver innovative applications and services to its merchants.

Value Results:

• Decentralized, self-service data access: Empowered teams to access and utilize data independently.

• Streamlined data streaming adoption: Facilitated the implementation of real-time analytics use cases across the organization.

• Reusable data products: Enabled the creation of valuable data products for internal users and customers.

• Accelerated innovation: Reduced bottlenecks and fostered a more agile and data-driven environment.