Flex Conference (Physical / Digital)

International Conference on Data Engineering and Information Systems - (ICDENIS-27)

23rd - 24th March 2027 , Edinburgh - UK

Registration Options

Access Flexible Participation Categories

Call For Papers

The (ICDENIS-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Information Science are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Data engineering for big data applications
  • Information systems architecture and design
  • Data integration techniques and challenges
  • Real-time data processing frameworks
  • Data warehousing and analytics solutions
  • Cloud-based data engineering practices
  • Data governance and management strategies
  • Data quality assurance methodologies
  • NoSQL databases and their applications
  • Data engineering for machine learning
  • Data pipelines and workflow automation
  • Data modeling techniques in information systems
  • Data visualization for decision making
  • Data ethics and compliance issues
  • Data engineering in IoT ecosystems
  • Distributed systems for data processing
  • Scalable data architectures for enterprises
  • Data engineering in financial services
  • Trends in information systems development
  • Future directions in data engineering

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.