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Real-time streaming & event-driven architecture

Event-driven architecture: the foundation for a business that acts on what is happening now, not what happened yesterday.

Most enterprise data still moves in batches. Files collected, processed overnight, loaded into systems by morning. It worked – when decisions could wait. The organisations pulling away from their competitors in financial services, retail, logistics, and media are not waiting anymore. They have rebuilt their data architecture around continuous, event-driven flows – data that moves the moment something happens and reaches the systems that need to act on it in milliseconds.

Dot Group designs and delivers streaming and event-driven architectures that make real-time data a practical reality rather than an aspiration.

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From batch to event-driven

The shift from batch to event-driven architecture is not a single project, it is a series of decisions about which data flows need to move faster, and what the right architecture looks like for each one. Fraud detection needs sub-millisecond latency. Inventory management might need updates every few minutes. Customer personalisation sits somewhere in between.

We start with your use cases, not with a technology preference. That means assessing where batch is still appropriate, where it is creating a bottleneck, and where moving to continuous, event-driven pipelines would create measurable business value. The output is an architecture that matches the speed requirement of each workload and a programme that sequences the transition without disrupting the operations that depend on what you have today.

The streaming backbone

Confluent, now part of IBM, is the world’s leading data streaming platform, built by the original creators of Apache Kafka and re-engineered for enterprise scale in the cloud. Where open-source Kafka requires significant operational overhead to run reliably at scale, Confluent delivers a fully managed, cloud-native streaming platform with a 99.99% uptime SLA, automated scaling, and the governance and compliance capabilities that enterprise workloads require.

For organisations already running Confluent or Kafka, we extend and optimise what is there – platform health checks, identifying event-driven patterns that are not yet being exploited, and building the roadmaps for wider adoption. For organisations coming to streaming for the first time, we deliver the full architecture from use case validation through to production deployment.

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Intelligent data ingestion at the source

Real-time streaming architecture needs a reliable, intelligent layer to get data from its sources into the streaming backbone – handling transformation, enrichment, and quality checks that raw event data requires before it is useful. IBM StreamSets does this at scale, with pipelines that adapt automatically when source systems change, and a unified control plane that makes pipeline creation and governance consistent across every data source.

StreamSets integrates directly with Confluent, feeding event streams with the quality and consistency that downstream analytics and AI applications depend on. Together they form the data engineering layer that sits beneath every real-time use case we deliver.

The Dot Group Advantage

Dot Group is a leading delivery partner for both Confluent and IBM StreamSets, two of the core technologies in IBM’s data streaming portfolio. Our team has designed and delivered real-time and event-driven architectures across financial services, retail, logistics, and media, and we understand the organisational as well as the technical complexity of making the shift from batch to streaming.

We stay with the architecture as it scales, work through the edge cases that only emerge in production, and provide the ongoing support that keeps event-driven systems performing as the business grows.

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Find out where real-time data would make the biggest difference to your business.

We will map your current architecture, identify the use cases where event-driven data would create the most value, and show you what the right approach looks like.

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