- Big Data Conference Europe 2026 will examine production-ready AI, advanced data systems and engineering challenges
- Vilnius will host experts exploring agentic workflows, real-time architectures, secure AI and scalable infrastructure on November 24–27th
- Practical workshops will cover streaming, GenAI-ready data, ETL testing, Spark, and AI strategy
- International speakers will share insights across data engineering, analytics, cybersecurity, cloud platforms, and artificial intelligence
The 10th edition of Big Data Conference Europe will take place in Vilnius and online on November 24–27th and focus on data engineering, AI systems, real-time architectures, autonomous workflows and operational scale. The four-day conference will feature more than 90 talks and workshops across six tracks, with more than 700 attendees expected from over 35 countries.
The event will begin with a dedicated workshop day on November 24th at Simbiocity Nova, followed by three conference days at Forum Cinemas Vingis and online. This year’s edition will be co-located with AI Summit Europe 2026, with a single ticket providing access to both programmes and extending the agenda from technical data infrastructure to AI strategy, implementation and enterprise use cases.
From AI Experiments to Production Systems
A central theme for 2026 is the shift from experimental AI demonstrations toward stable systems operating reliably in production. The agenda will examine advanced RAG architectures, agentic workflows, LLM fine-tuning and prompt engineering, system evaluation and benchmarking, as well as observability across GenAI pipelines.
Data engineering sits at the foundation of these systems, and the Conference will explore how pipelines and DataOps practices need to evolve for AI workloads. Sessions will address real-time and streaming architectures, AI-ready data modelling, secure AI systems and the infrastructure required to support increasingly autonomous applications.
The focus extends beyond individual technologies toward the organizational challenges surrounding them. Scaling AI and data teams, managing operational complexity, and controlling infrastructure costs will get featured alongside technical discussions, reflecting the growing gap between experimenting with AI and engineering it at scale.
AI Agents Move Into the Data Stack
AI agents and autonomous workflows will form another major strand of the 2026 programme, as AI systems increasingly move beyond conversational interfaces toward execution. Topics include multi-agent architectures, tool calling and function execution, autonomous data workflows, and AI copilots for developers and analysts.
The Conference will also examine the guardrails and control mechanisms needed as these systems gain greater autonomy. This includes questions around data security, observability, evaluation and the management of risk when AI systems can make decisions or initiate actions with limited human intervention.
MLOps and LLMOps will provide the operational layer for these developments, with the programme examining how organizations can move from experimentation toward repeatable and maintainable AI engineering practices. Cost optimization will be another consideration, particularly as organizations contend with finite GPU resources and the growing computational demands of modern AI systems.
Modern Data Infrastructure Under Pressure
The evolution of the modern data stack will receive dedicated attention as organizations manage increasingly complex combinations of cloud platforms, streaming infrastructure, machine learning systems, and analytics tools. The programme will explore how all these components can be designed and operated as coherent production environments rather than isolated technology projects.
Real-time data will be particularly important as businesses increasingly require systems capable of reacting immediately to events. The workshop programme will address this directly through End-to-End Real-Time Data Pipeline: From Ingestion to Insights and Low-code Streaming Analytics with Apache Flink.
Other hands-on sessions will focus on building GenAI-ready lakehouses on AWS, optimizing Spark pipelines and testing ETL data pipelines. A further workshop, Building the Bank’s Memory. Store Data Forever. Replay Any Point in Time, will examine approaches to persistent data storage and historical replay.
Data Security and Responsible AI
As AI systems become more autonomous, security and governance become increasingly connected to data engineering. Big Data Conference Europe 2026 will address data security and secure AI systems alongside the technical architecture needed to control risk and maintain reliable operations.
The Conference’s wider speaker programme also includes subjects such as AI ethics, cybersecurity, explainable AI, federated learning, distributed systems, data mesh, edge computing, and cloud-native technologies. These areas reflect the event’s broader focus on the infrastructure and engineering principles underpinning modern data and AI systems.
AI-driven organizational transformation will provide another perspective, examining the changes required when AI adoption affects technical architecture just as much as teams, workflows, and decision-making. The emphasis will be placed on how organizations can scale their capabilities alongside the technologies they deploy.
International Speakers and Technical Workshops
The 2026 keynote lineup includes Thomas Endres, Managing Partner at TNG Technology Consulting; Šarūnas Chomentauskas, CEO of Exacaster; Peter Mesarec, CEO of SEOS AI; Stefan Chiriacescu, Co-founder and CEO of eCommerce Today Agency; Aistis Raudys, CEO of AAI Labs; and Darren Richardson, Senior CyberSecurity Engineer at ICEYE. Their perspectives span AI, data, cybersecurity, technology consulting, and digital business.
The wider speaker roster includes Niels Claeys of Data Minded, Nensi Hakobjanyan of AWS, Andrew Madson of Fivetran, Alex Tasioulis of Thrive Learning, Martynas Jočys of Macaw, Mahavir Teraiya of Databricks, Viktoriia Kniazeva of Omnevo, and Jan Ypma of Ypma Consulting. The international lineup reflects the Conference’s focus on practical engineering experience across data platforms, analytics, cloud and AI.
The November 24th workshops will provide a practical counterpart to the conference sessions, allowing participants to work directly with technologies and approaches discussed throughout the event. Together, the seven workshops cover real-time pipelines, GenAI-ready data, Apache Flink, ETL testing, Spark optimization, AI strategy and persistent data architectures.
In a Nutshell
- Date: November 24–27th, 2026
- Place: Forum Cinemas Vingis and Simbiocity Nova, Vilnius, Lithuania
- Tickets here
- More information: at the Conference’s official website
- For additional Inquiries: info@cyberwisecon.eu
Big Data Conference Europe 2026 will share its Vilnius venue and dates with AI Summit Europe, creating an expanded four-day technology event covering both data engineering and applied AI. Attendees with a conference ticket can access both programmes, with Big Data Conference Europe focusing on data engineering, DataOps, real-time systems, data platforms, cloud and MLOps, while AI Summit Europe adds AI strategy, agents, automation, responsible AI and enterprise implementation.
Kostiantyn is a freelance writer from Crimea but based in Lviv. He loves writing about IT and high tech because those topics are always upbeat and he’s an inherent optimist!
