Popescu, Mirona Ana-Maria, Ge, Mouzhi and Helfert, Markus (2019) The Social Media Perception and Reality-Possible Data Quality Deficiencies between Social Media and ERP. In: Proceedings of the 20th International Conference on Enterprise Information Systems (ICEIS 2018). SciTePress: Science and Technology Publications, Lda, pp. 198-204. ISBN 9789897582981
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Abstract
With the increase of digitalisation, data in social media are often seen as more updated and realistic than the
information system representations. Due to the fast changes in the real world and the increasing Big Social
media data, there is usually certain misalignment between the social media and information system in the
enterprise such as ERP, therefore there can be data deficiencies or data quality problems in the information
systems, which is caused by the differences between the external social media and internal information
system. In this paper, underpinned by the work of ontological data quality from Wang and Wand 1996, we
investigate a set of data quality problems between two representations - Social Media and ERP. We further
discuss how ERP system can be improved from the data quality perspective.
Item Type: | Book Section |
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Additional Information: | This work was supported, in part, by Science Foundation Ireland grant 13/RC/2094 and co-funded under the European Regional Development Fund through the Southern & Eastern Regional Operational Programme to Lero - the Irish Software Research Centre (www.lero.ie) |
Keywords: | Data Quality; ERP; Social Media; Business Intelligence Solutions; |
Academic Unit: | Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI Faculty of Social Sciences > School of Business |
Item ID: | 13438 |
Identification Number: | 10.5220/0006788801980204 |
Depositing User: | Markus Helfert |
Date Deposited: | 09 Oct 2020 16:39 |
Publisher: | SciTePress: Science and Technology Publications, Lda |
Refereed: | Yes |
Funders: | Science Foundation Ireland (SFI), European Regional Development Fund |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/13438 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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