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Big Data Quality: From Content to Context | ||
| Journal of Information Technology Management | ||
| مقاله 5، دوره 10، شماره 4، 2018، صفحه 64-71 اصل مقاله (499.52 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jitm.2019.72762 | ||
| نویسنده | ||
| Ahmad Khalilijafarabad* | ||
| PhD, Department of Information Technology Management, Faculty of Management, University of Tehran, Tehran, Iran. | ||
| چکیده | ||
| Over the last 20 years, and particularly with the advent of Big Data and analytics, the research area around Data and Information Quality (DIQ) is still a fast growing research area. There are many views and streams in DIQ research, generally aiming at improving the effectiveness of decision making in organizations. Although there are a lot of researches aimed at clarifying the role of BIG data quality for organizations, there is no comprehensive literature review that shows the main differences between traditional data quality researches and Big Data quality researches. This paper analyzed the papers published in Big data quality and find out that there is almost no new mainstream about Big Data quality. It is shown in this paper that the main concepts of data quality does not changes in Big Data context and that only some new issues have been added to this area. | ||
| کلیدواژهها | ||
| Big data؛ Big data quality؛ Data quality؛ Text mining | ||
| مراجع | ||
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