Building Data Infrastructure That Works
We help organizations design and implement reliable, scalable data systems that support business growth
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DataStream was established in Cyprus with a clear focus on addressing the growing complexity of data infrastructure challenges faced by modern organizations. Our founding team recognized that many businesses were struggling to manage increasing data volumes while maintaining system reliability and performance.
From our first project implementing a data pipeline for a financial services firm, we have maintained our commitment to technical rigor and practical solutions. We focus on understanding each client's specific operational context, technical constraints, and business requirements before proposing architectural approaches.
Our work spans organizations of various sizes and sectors, from technology startups requiring scalable ingestion systems to established enterprises modernizing legacy data platforms. Each engagement has reinforced our belief that effective data engineering requires balancing technical capabilities with operational realities.
Based in Limassol, we serve clients throughout Cyprus and internationally, bringing expertise in modern data engineering practices while respecting the unique requirements and constraints of each implementation environment. Our approach emphasizes sustainable solutions that teams can maintain and evolve as needs change.
Our Methodology
We follow systematic approaches grounded in established data engineering principles and industry standards
Requirements Analysis
We begin each engagement with detailed examination of existing data flows, system constraints, and business requirements. This includes analysis of data sources, volumes, velocity patterns, and downstream consumption needs. We document current pain points, performance bottlenecks, and specific objectives for the new implementation.
Architecture Design
Based on gathered requirements, we design system architectures using appropriate patterns and technologies. Our designs consider scalability requirements, fault tolerance needs, data quality expectations, and operational constraints. We evaluate multiple architectural approaches and recommend solutions that balance technical capabilities with practical implementation considerations.
Implementation & Testing
We implement systems following engineering best practices including version control, code review, and automated testing. Each component undergoes unit testing, integration testing, and performance validation. We establish monitoring and alerting before production deployment, ensuring operational visibility from the start.
Documentation & Knowledge Transfer
Complete documentation accompanies every implementation, including architecture diagrams, data flow documentation, operational runbooks, and troubleshooting guides. We conduct knowledge transfer sessions with your team, covering system operation, monitoring interpretation, and common maintenance procedures. This ensures your team can effectively operate and maintain the system independently.
Our Team
Experienced data engineers committed to delivering reliable, maintainable solutions
Eleni Constantinou
Specializes in designing scalable data pipeline architectures and cloud infrastructure patterns. Has implemented data platforms for organizations processing terabytes of data daily across various industries.
Marios Theodosiou
Focuses on stream processing systems and real-time data infrastructure. Expert in building low-latency data pipelines and implementing complex event processing for time-sensitive applications.
Andreas Georgiou
Specializes in cloud platform migrations and infrastructure optimization. Has guided numerous organizations through successful transitions from on-premise to cloud-based data infrastructure.
Our Values & Approach
Reliability First
We prioritize system reliability and data integrity in all our implementations. Our architectures include appropriate error handling, retry logic, and fault tolerance mechanisms. We believe that reliable systems provide more value than complex systems that fail unpredictably.
Practical Solutions
We focus on solutions that address actual business needs rather than implementing technology for its own sake. Our recommendations consider operational capabilities, team skills, and maintenance requirements alongside technical requirements. We aim for systems that teams can understand, operate, and modify as needs evolve.
Performance Optimization
We design systems with performance requirements in mind from the start. This includes appropriate partitioning strategies, efficient data formats, and optimization of computational resources. We conduct performance testing before production deployment and provide guidance on monitoring and tuning production systems.
Knowledge Transfer
We ensure your team can effectively operate and maintain implemented systems. This includes comprehensive documentation, training sessions, and ongoing support during the transition period. We believe that successful projects result in capable, confident teams who understand their systems thoroughly.
Ready to Work Together?
Let's discuss your data infrastructure needs and explore how we can help
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