Conference Description
Key Takeaways
- International academic conference exploring the convergence of database systems, artificial intelligence, and data analytics
- Covers data mesh, data fabric, large language models, MLOps, and quantum technologies for data engineering
- Addresses data governance, privacy, security, and pipeline automation challenges
- Designed for researchers, data engineers, data scientists, and IT professionals across finance, healthcare, manufacturing, and security sectors
- Takes place in Graz, Austria from August 11–13, 2026
Introduction
DEXA 2026, the 37th International Conference on Database and Expert Systems Applications, convenes researchers, practitioners, and technologists working at the intersection of data engineering, artificial intelligence, and advanced analytics. Now in its fourth decade, the conference continues to serve as a significant venue for presenting peer-reviewed research and discussing practical applications in database systems and knowledge management. The 2026 edition arrives at a moment when organisations across industries face mounting pressure to extract value from increasingly complex data environments while navigating evolving requirements around governance, privacy, and AI integration.
About This Event
The conference takes place in Graz, Austria over three days in August 2026. As an in-person event, DEXA provides opportunities for direct engagement through paper presentations, keynote addresses, and associated workshops. The programme maintains a technical and research-oriented focus, with proceedings published through Springer’s Lecture Notes in Computer Science series. Academic journals including Knowledge and Information Systems and Data & Knowledge Engineering are also associated with the conference.
The Convergence of AI, Data Engineering, and Analytics
A central theme running through DEXA 2026 is the growing interdependence between artificial intelligence and data engineering disciplines. As organisations deploy machine learning models at scale, the underlying data infrastructure becomes increasingly critical. This relationship works in both directions: AI techniques now inform how data systems are designed and optimised, while robust data engineering practices determine whether AI initiatives succeed in production environments.
The conference programme reflects this convergence through topics spanning AI model governance, AutoML, and MLOps alongside traditional database concerns. Large language models receive particular attention, reflecting their rapid adoption across enterprise applications and the distinct data management challenges they present. Sessions also examine how AI can enhance data quality assessment, automate pipeline orchestration, and improve query optimisation.
Architectural Approaches to Modern Data Challenges
DEXA 2026 addresses several architectural paradigms that have gained prominence as organisations grapple with distributed, heterogeneous data environments. Data mesh and data fabric represent two distinct approaches to managing data at scale—the former emphasising domain-oriented ownership and federated governance, the latter focusing on unified access layers and automated integration. Understanding the trade-offs between these architectures has become essential for organisations designing systems that must balance autonomy with consistency.
The programme also covers distributed ledger technologies, real-time data processing, and cloud data management. These topics connect to broader discussions around Data-as-a-Service and Compute-as-a-Service models, which continue to reshape how organisations provision and consume data infrastructure. Emerging research into quantum technologies for data engineering and analytics points toward longer-term developments that may fundamentally alter computational approaches to data-intensive problems.
Governance, Privacy, and Operational Concerns
Beyond architectural considerations, the conference dedicates significant attention to governance and operational challenges. Data quality remains a persistent concern, particularly as organisations integrate diverse sources and deploy automated decision-making systems. Privacy and security requirements continue to evolve in response to regulatory developments and growing awareness of data protection risks.
Data pipeline automation represents another area of active research, as manual approaches struggle to keep pace with the volume and velocity of modern data flows. The conference examines how organisations can build reliable, observable pipelines while maintaining appropriate controls over data lineage and access.
Who Should Attend
DEXA 2026 serves academic researchers and industry practitioners alike. University faculty, research scientists, and doctoral students will find opportunities to present work and engage with peers across the database and AI research communities. Data engineers, data scientists, and machine learning engineers working in applied settings can gain exposure to emerging techniques and architectural approaches. The conference also attracts database administrators, R&D managers, and technical leaders responsible for data strategy within their organisations. Attendees typically come from universities, research institutes, technology companies, and enterprises in sectors including finance, healthcare, manufacturing, and security.