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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


CO-CHAIRS

Orlando Belo
University of Minho
Portugal
 
Brief Bio
Orlando Belo (http://www.di.uminho.pt/~obelo) is currently an Associate Professor, with Habillitation, at the Department of Informatics of the School of Engineering of the University of Minho and a researcher at the ALGORITMI / LASI R&D Center, at the same university. Its main activities, both teaching and research, are essentially in the field of Database Systems, Business Intelligence and Operational Intelligence, with particular emphasis on disciplines such as Databases, Data Warehousing, Analytical Processing, Data Visualization and Data Analysis. He began his career as a higher education professor in December 1986 at the University of Minho, an institution in which he still continues to develop his professional activities. He graduated in 1986 in Systems Engineering and Informatics from the University of Minho, in 1998 he received his PhD, from the University of Minho, in Informatics - Distributed Artificial Intelligence and Multiagent Systems -, and in 2013 he did his Habillitation in Informatics - Data Warehousing Systems - at the University of Minho. During the last few years, he has published several articles, with selection, at conferences, mostly at international events, which were developed within the scope of his main areas of research, teaching and industrial experiences. He is a consultant for the University of Minho, through processes of providing specialized services to the community, developing activities of analysis, planning and development of analytical systems. Between November 2012 and November 2016 he was director of the Department of Informatics at the School of Engineering of the University of Minho.
Bruno Oliveira
Porto Polytechnic
Portugal
 
Brief Bio
My academic journey is rooted in Informatic Engineering and computer science, specializing in data management, data transformation, and Business Intelligence systems. I hold a Bachelor's degree in Informatic Engineering (2009), a Master of Informatic Engineering (2012) from the School of Management and Technology at Porto Polytechnic, and a PhD in Informatics (2018) from the University of Minho – School of Engineering. Since 2010, my passion for education has led me to teach at the School of Management and Technology – Porto Polytechnic, starting as an Invited Assistance Professor until 2018, advancing to Invited Adjunct Professor from 2018 to 2022, and currently serving as an Adjunct Professor since 2022. Additionally, I served as an Invited Assistant Professor at the University of Minho from 2014 to 2018 and was invited by ISCTE to teach master’s degree courses from 2018 to 2021. My involvement in research start as a Collaborator at the CIICESI research center from 2010 to 2018, and becoming an integrated member since 2018. Similarly, I contributed to the ALGORITMI research center as a collaborator from 2012 to 2018. Throughout my academic and scientific path, I have concentrated on various facets of data analytics, particularly in Business Intelligence Systems, Data Warehousing, data transformation, data quality monitoring, and data processing. This dedication is evident in my 38 scientific publications in international conferences and journals. Engaging in research projects has been a fulfilling aspect of my career, contributing to the RAID B2K project between 2014 and 2015, and more recently, SmartLex between 2021 and 2023, and PRODUTECH R3 since 2023. In parallel with my academic career, I have taken on several management roles within academia. Since 2019, I have served as a member of the pedagogical council at the School of Management and Technology and as a Subdirector of the Informatics Department. In the 2018/2019 academic year, I held the position of director for the "Curso Técnico Superior Profissional" degree in Informatics and Management, and in 2017/2018, I was a coordination member for the same course.
Óscar Oliveira
CIICESI - Porto Polytechnic - School of Management and Technology
Portugal
 
Brief Bio
Óscar de Oliveira holds a degree in Computer Science - Applied Mathematics, conferred by Universidade Portucalense Infante D. Henrique in 2001. Subsequently, he attained a master’s degree in computer engineering from the School of Management and Technology at the Polytechnic Institute of Porto in 2012. In 2019, he completed the PhD Program in Industrial Engineering and Management at the Faculty of Engineering of the University of Porto, with a specific focus on heuristics for two-dimensional cutting and packing problems. His professional trajectory began as a systems analyst for the development of digital platforms for industrial programming, business-to-business (B2B), and business-to-consumer (B2C) applications. Notably, the B2B and B2C platforms he contributed to were tailored for international markets, particularly in the domain of fashion products. Óscar de Oliveira entered the field of education in 2006, initially serving as an educator in primary and secondary education. In 2013, he transitioned to higher education at the School of Management and Technology. Óscar de Oliveira is an integral member of the Center for Innovation and Research in Business Sciences and Information Systems. His primary research interests revolve around solving combinatorial optimization problems prevalent in various fields, including cutting and packaging problems and location problems. Óscar employs heuristic and metaheuristic approaches to address these challenges. Given the interdisciplinary nature of the research center, he has collaborated with researchers from diverse domains, leading to the publication of articles spanning multiple research areas.

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).

SECRETARIAT CONTACTS

ICEIS Workshops - BI-DEMT 2025
e-mail: iceis.secretariat@insticc.org
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