Business Process Management Based on Big Data Analytics
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 January 2026 | Viewed by 396
Special Issue Editors
Interests: business intelligence, business process management (BPM), data analytics, information visualization, big data
Special Issue Information
Dear Colleagues,
This Special Issue of Systems focuses on business process management (BPM) based on big data analytics. This is an emerging topic that leverages the vast amounts of data generated by modern organizations to optimize, monitor, and improve business processes. By integrating big data analytics into BPM, organizations can extract valuable insights from structured and unstructured data to enable better decision making, process automation, continuous process improvement, and operational efficiency by tracking key performance indicators (KPIs) in real time, enabling proactive adjustments and more precise alignment with strategic goals.
Integrating artificial intelligence (AI) into this synergy amplifies its impact by enabling advanced predictive modeling, intelligent process automation, and improved decision making, as well as anticipating process inefficiencies and uncovering hidden patterns in data that would otherwise go unnoticed. As organizations across industries embrace AI, it is increasingly seen as a transformative tool that enables greater agility, customer focus, and competitiveness in today's data-driven landscape.
For this Special Issue, we are seeking papers that are relevant to the BPM community, as well as to big data analytics researchers and practitioners in various industries. Papers are sought in the following areas (but are not limited to these):
- Real-time process monitoring and optimization;
- Predictive analytics in BPM;
- Process mining and big data;
- Data-driven decision making;
- BPM automation and AI integration;
- Customer-centric process personalization;
- Security and privacy in data-driven BPM.
Dr. Jorge Oliveira e Sá
Dr. José Luis Mota Pereira
Guest Editors
Manuscript Submission Information
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Keywords
- business process management
- big data
- decision making
- data analytics
- AI integration
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