Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/16410
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dc.contributor.authorWijayatunga, P.-
dc.date.accessioned2017-02-15T09:08:22Z-
dc.date.available2017-02-15T09:08:22Z-
dc.date.issued2016-
dc.identifier.citationWijayatunga, P. 2016. Data Deluge and Its Analysis Issues. In Proceedings of the 2nd International Conference in Accounting Researchers and Educators (ICARE 2016), 11th January 2017. Department of Accountancy, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka.en_US
dc.identifier.issn2465- 6046-
dc.identifier.urihttp://repository.kln.ac.lk/handle/123456789/16410-
dc.description.abstractCurrent availability of enormous amount of data is mainly due to technological advances. They are useful drawing inferences for creating new businesses, formulation of new policies or revising existing ones, etc. However, much of analyses are performed either by subject domain experts implementing mathematical and computational models incorrectly or by mathematical and computational professionals, purely on data driven basis without paying required attention to the subject domain knowledge. Both of these exercises often result in incorrect inferences and therefore they may harm the society, especially when their inferences are used in practice. We argue that, in order to get valid inferences these two parties should work together. Here we briefly discuss some of the issues that the large-scale data analyses should take into account, especially in open data and big data. We also briefly discuss our solutions that are rather simple to implement.en_US
dc.language.isoenen_US
dc.publisherDepartment of Accountancy, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lankaen_US
dc.subjectOpen dataen_US
dc.subjectBig dataen_US
dc.subjectStatisticalen_US
dc.subjectCausalen_US
dc.subjectInferenceen_US
dc.titleData Deluge and Its Analysis Issuesen_US
dc.typeArticleen_US
Appears in Collections:ICARE 2016

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