Analytical Intelligence in Processes: Data Science for Business

Analytical Intelligence in Processes: Data Science for Business

The recent attention for Big Data illustrates that organizations are aware of the potential of the torrents of data generated by today's information systems. Despite increasing interest regarding to Big Data and analytics tools, to the best of our knowledge, there are no studies cover and class...

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Bibliographic Details
Published in:Revista IEEE América Latina Vol. 16; no. 8; pp. 2240 - 2247
Main Author: Rocha Silva, Fernanda Aparecida
Format: Journal Article
Language:English
Portuguese
Published: Los Alamitos IEEE 01-08-2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Analytics
Big Data
Big Data Analytics
Business
Business Process Intelligence
Data management
Data mining
Data science
IEEE transactions
Intelligence
Mathematical analysis
Process Mining
Process Warehouse
Torrents
Visualization
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Summary:The recent attention for Big Data illustrates that organizations are aware of the potential of the torrents of data generated by today's information systems. Despite increasing interest regarding to Big Data and analytics tools, to the best of our knowledge, there are no studies cover and classify the types of research being published specifically on analytical intelligence in processes associated with data science tools. As a first step towards bridging this gap, we carried out a systematic mapping to synthesize an overview of the area. We went through 351 papers on theme. Among them, 63 were related to analytical intelligence in processes and only 38 met the criteria for inclusion and exclusion of articles defined in this study. These 38 papers were selected and categorized according to their contribution. As a result, a chart of the area was developed and the most investigated topics were identified indicating that most studies focus on investigating how analytical intelligence in processes can be used to discovery, conformance checking, model repair and enrich, role discovery, bottleneck analysis, monitoring of events, frauds audit, predicting the remaining flow time, and recommending next steps.
ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2018.8528241