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2016 | OriginalPaper | Buchkapitel

5. Business Process Data Analysis

verfasst von : Seyed-Mehdi-Reza Beheshti, Boualem Benatallah, Sherif Sakr, Daniela Grigori, Hamid Reza Motahari-Nezhad, Moshe Chai Barukh, Ahmed Gater, Seung Hwan Ryu

Erschienen in: Process Analytics

Verlag: Springer International Publishing

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Abstract

This chapter looks at business process data analysis and provides an overview of different aspects of business data analysis techniques and approaches from process/dataspaces to data provenance and data-based querying techniques. After providing an overview of warehousing process data, data services, and dataspaces, the chapter discusses the importance of supporting big data analytics over process execution data. It presents a holistic view of the process executions over various information systems and services (i.e., process space) followed by a brief overview of process mining to highlight the interpretation of the information in the enterprise in the context of process mining. Finally, the chapter focuses on process artifacts and introduces crosscutting aspects in processes data such as time and provenance.

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Fußnoten
4
An iceberg cube contains only those cells of the data cube that meet an aggregate condition. It is called an iceberg cube because it contains only some of the cells of the full cube [76]
 
5
Skyline [478] has been proposed as an important operator for multi-criteria decision-making, data mining and visualization, and user preference queries
 
6
Linked data is a method of publishing data on the Web based on principles that significantly enhance the adaptability and usability of data, either by humans or machines [84]
 
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Metadaten
Titel
Business Process Data Analysis
verfasst von
Seyed-Mehdi-Reza Beheshti
Boualem Benatallah
Sherif Sakr
Daniela Grigori
Hamid Reza Motahari-Nezhad
Moshe Chai Barukh
Ahmed Gater
Seung Hwan Ryu
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-25037-3_5

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