Systems Perspectives on Data Engineering Challenges in AI-Driven Business Intelligence
A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".
Deadline for manuscript submissions: 31 August 2026 | Viewed by 5
Special Issue Editors
Interests: data warehouse; ETL/data integration; data quality; data analytics and business intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: combinatorial optimization; data quality and data analytics; information systems; industrial data processing; smart manufacturing systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Organizations increasingly rely on complex data ecosystems to support digital transformation and informed decision-making. Modern data warehouses, ETL and data integration pipelines, and AI-augmented analytics platforms now operate as interconnected socio-technical systems, requiring holistic and systemic perspectives. This Special Issue invites contributions that examine how system-oriented methodologies—such as systems thinking, systems engineering, system dynamics, and cyber–physical information systems—can enhance the design, operation, and governance of data-centric architectures.
We aim to explore how integrated data workflows, data quality frameworks, metadata management, knowledge graphs, and AI and machine learning techniques can be combined to create robust and adaptive business intelligence environments. Submissions addressing system-level challenges such as scalability, interoperability, data governance, automation, explainability, and resilience in data pipelines are particularly welcome.
This topic aligns within the scope of Systems as it investigates the interactions, structures, feedback loops, and emergent behaviours of data and analytical systems within real-world organizational contexts. Through systemic approaches, we aim to advance understanding of how data infrastructures can support innovation, operational excellence, and sustainable digital transformation.
Dr. Bruno Oliveira
Dr. Óscar Oliveira
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- data warehousing
- ETL
- data integration
- data quality
- business intelligence
- data engineering
- systems thinking
- system dynamics
- AI and machine learning
- digital transformation
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