Workshop
Workshop on Data Engineering Models and Techniques for Business Intelligence and Enterprise Applications -
BI-DEMT
2025
4 - 6 April, 2025 - Porto, Portugal
In conjunction with the 27th International Conference on Enterprise Information Systems - ICEIS 2025
* CANCELLED *
CO-CHAIRS
|
Orlando Belo
University of Minho
Portugal
|
|
|
|
Brief Bio
Orlando Belo is an associate professor with habilitation in the Department of Informatics at Minho University, Portugal. He is also a member of the Algoritmi R&D Centre in the same university, working in areas like Data Warehousing Systems, OLAP, and Data Mining. His main research topics are related with data warehouse design, implementation and tuning, ETL services, and distributed multidimensional structures processing. During the last few years he was involved with several projects in the decision support systems area designing and implementing computational platforms for specific applications like fraud detection and control in telecommunication systems, data quality evaluation, and ETL systems for industrial data warehousing systems. More recently, he was developing some research work establishing OLAP usage profiles and optimizing OLAP selection methods incorporating knowledge acquired over OLAP user sessions and users’ preferences.
|
|
Bruno Oliveira
CIICESI, School of Management and Technology, Porto Polytechnic, Portugal
Portugal
|
|
|
|
|
|
|
Óscar Oliveira
CIICESI - Porto Polytechnic - School of Management and Technology
Portugal
|
|
|
|
|
SCOPE
In today's digital era, organizations face high-volume, complex data from diverse sources. This rapid growth demands advanced data engineering solutions for seamless ingestion, integration, and transformation into actionable insights. Traditional approaches often struggle with dynamic business needs, real-time decisions, and scalability.
Artificial Intelligence (AI) is revolutionizing data engineering, reshaping data pipelines and architectures. Through machine learning, generative AI, and automation, AI tackles challenges like data quality, anomaly detection, and metadata management, while accelerating processes and enabling new paradigms like stream analytics and knowledge discovery.
This workshop explores AI-driven innovations in data engineering for enterprise systems and business intelligence. Focus areas include AI-enhanced pipelines, real-time processing, and adaptive architectures, bridging theoretical advances and practical applications for enterprise-scale decision-making.
TOPICS OF INTEREST
Topics of interest include, but are not limited to:
- AI-Enhanced Data Engineering
- Intelligent Architectures and Models
- Real-Time Data Processing and Stream Analytics
- Data Integration and Enterprise Systems
- Business Intelligence Applications
- Data Ethics, Security, and Governance
- Future Trends and Emerging Challenges
IMPORTANT DATES
Paper Submission:
January 30, 2025
Authors Notification:
February 13, 2025
Camera Ready and Registration:
February 21, 2025
WORKSHOP PROGRAM COMMITTEE
Available soon.
PAPER SUBMISSION
Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at: Paper Templates
Please also check the Guidelines.
Papers must be submitted electronically via the web-based submission system using the appropriated button on this page.
PUBLICATIONS
After thorough reviewing by the workshop program committee, all accepted papers will be published in a special section of the conference proceedings book - under an ISBN reference and on digital support.
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library (http://www.scitepress.org/DigitalLibrary/).
SCITEPRESS is a member of CrossRef (http://www.crossref.org/) and every paper is given a DOI (Digital Object Identifier).