On Predictive Big Data Quality

Businesses process use data to produce services and or goods, and most importantly for developing business strategies as part of data driven change management approach. The goodness of the data used is an important factor regarding process lead time, customer satisfaction and service quality. The main contribution of this work is to define a big data quality conceptual framework related to business process performance as part of an online analytical, predictive mining framework. Here we consider the domain of Mellitah Oil & Gas (MOG), in Libya.

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Publication Details

Published
2024-08-29
DOI
https://doi.org/10.1109/is61756.2024.10705180
Citations
1
Primary Topic
Data Mining Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.78
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article

On Predictive Big Data Quality

François Roubert, Panagiotis Chountas, Ismael Rhemat
1 citations
Data Mining Algorithms and Applications
0.78
article

On Predictive Big Data Quality

François Roubert, Panagiotis Chountas, Ismael Rhemat
article en
1 citations

Abstract

Businesses process use data to produce services and or goods, and most importantly for developing business strategies as part of data driven change management approach. The goodness of the data used is an important factor regarding process lead time, customer satisfaction and service quality. The main contribution of this work is to define a big data quality conceptual framework related to business process performance as part of an online analytical, predictive mining framework. Here we consider the domain of Mellitah Oil & Gas (MOG), in Libya.

University of Westminster (GB)
Openalex Percentile: Top 20%
Data Mining Algorithms and Applications
0.78
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On Predictive Big Data Quality — François Roubert, Panagiotis Chountas, et al. · (2024) | TGRS Research Map | TGRS