Data Integration and Governance in Business Intelligence Systems
A special issue of Systems (ISSN 2079-8954).
Deadline for manuscript submissions: 30 April 2025 | Viewed by 1784
Special Issue Editors
Interests: data warehouse; ETL/data integration; data quality; data analytics and business intelligence
Interests: optimization; ETL/data integration; data quality
Special Issue Information
Dear Colleagues,
Data governance refers to the sets of practices, policies, and procedures used to improve data quality, integrity, and security. As organizations and individuals continue to produce, share, and leverage vast amounts of data, the importance of robust data governance cannot be overstated. From personal information to organizational assets, data have come to constitute a critical resource driving innovation and decision making. This growth raises significant challenges, not only in data usage but also in related processing and storage processes, making effective data governance more crucial than ever. Data governance provides a framework to organize the data that are integrated, transformed, and used for business intelligence activities.
This Special Issue invites scientific contributions proposing new, innovative, and original approaches for the development of business intelligence using data governance practices. This Issue aims to provide an opportunity for academics and practitioners to share their theoretical and practical knowledge and findings in the field.
This Special Issue particularly looks forward to articles presenting, among others:
- Artificial intelligence applied to business intelligence and data governance.
- Business intelligence, business analytics and data integration.
- Data catalogs and active metadata.
- Semantic data and knowledge graphs.
- Inception and development of modern data architectures for data lakes, data warehouses, data lakehouses, data meshes and vaults.
- Data quality, curation provenance, security and their role in business intelligence systems.
- Innovative approaches and challenges for data integration.
- Data governance applications for learning, finance, marketing, banking, medicine, industry and services.
Dr. Bruno Oliveira
Dr. Óscar Oliveira
Dr. Telmo Matos
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 100 words) can be sent to the Editorial Office for announcement on this website.
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 quality
- data integration
- business analytics
- data governance
- business intelligence
- data architectures
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