Conference Description
Key Takeaways
- Big Data Conference Europe 2026 marks the event’s tenth edition, running November 24–27 in Vilnius as a hybrid conference
- Six technical tracks span big data, high load systems, cloud infrastructure, data engineering, machine learning and artificial intelligence
- The programme includes more than 90 presentations and seven hands-on workshops
- Designed for data engineers, data scientists, developers, architects and technology leaders
- Attendance includes access to AI Summit Europe 2026
Introduction
Big Data Conference Europe returns to Vilnius in November 2026 for its tenth annual edition, offering data professionals and technology leaders an opportunity to examine the evolving landscape of large-scale data processing, cloud architecture and applied machine learning. The hybrid format accommodates both in-person and remote participants from an international audience spanning more than 35 countries, reflecting the increasingly distributed nature of modern data teams and the global demand for expertise in these domains.
About This Event
Running from November 24 to 27, 2026, Big Data Conference Europe is structured as a multi-track technical conference with an accompanying workshop programme. The event draws more than 700 attendees annually, positioning it as one of the larger gatherings focused specifically on data infrastructure and analytics in the European calendar. Participants receive combined access to AI Summit Europe 2026, allowing them to explore artificial intelligence topics alongside the core big data programme without requiring separate registration.
Technical Programme and Discussion Topics
The conference programme comprises more than 90 presentations distributed across six parallel tracks. These tracks address big data processing frameworks and architectures, high load systems capable of handling substantial throughput and concurrency demands, cloud infrastructure and platform services, data engineering practices for building reliable pipelines, and the increasingly intertwined fields of machine learning and artificial intelligence.
Seven workshops provide hands-on learning opportunities that complement the presentation tracks. This combination of theoretical discussion and practical application reflects the reality that data professionals must balance architectural understanding with implementation skills. As organisations continue to scale their data operations and integrate machine learning into production systems, the ability to move between strategic thinking and technical execution has become essential.
Industry Context
The convergence of big data infrastructure and artificial intelligence represents one of the defining technical challenges of the current period. Organisations that invested heavily in data lakes and warehousing over the past decade are now working to operationalise that data through machine learning models and generative AI applications. This transition demands new architectural patterns, revised approaches to data quality and governance, and closer collaboration between data engineers and machine learning practitioners.
High load systems remain a persistent concern as data volumes grow and real-time processing expectations increase. Cloud platforms have simplified certain aspects of scaling, but they have also introduced complexity around cost management, multi-cloud strategies and the integration of managed services with custom infrastructure. These operational realities form the backdrop against which the conference’s technical discussions take place.
Who Should Attend
The conference targets practitioners working directly with data systems, including data engineers responsible for pipeline development and infrastructure, data scientists building analytical and predictive models, software developers integrating data services into applications, and architects designing systems that must accommodate growth and changing requirements. Technology leaders seeking to understand current capabilities and emerging approaches will also find relevant content across the programme tracks.
The international composition of the audience, with participants from more than 35 countries, creates opportunities for cross-pollination of ideas and exposure to how different organisations and regions approach common technical challenges.