BSc. Economics MSc.Supply Chain & Operations Management
E07a (Yang Fujia)
+44 (0) 115 8431399
Year of Registration:
Expected Completion Date:
Primary Funding Source:
Vice Chancellors Research Scholarship (EU) & Business School Scholarship
Decision Making Support With Big Data Analytics
How can data from different sources be integrated to support decision making?
Traditional decision making support processes and mechanisms integrate data from single sources. However, nowadays, for typical business intelligence tasks (such as customer opinion mining), organisations have many different ways to capture huge volumes of data from a variety of different sources (transactional data, social media, survey data, internet of things, etc.).
Traditional analytical models based on single source data may only produce limited insights leading to biased decisions. At the same time, integrating data from multiple sources is a very challenging task that most businesses still do not know how to cope with. Not only so, it also appears that overloading a decision support model with too many variables does not often yield positive results. Thus, organisations are not only faced with the challenge of designing analytical models based on these multiple information sources, they also have to identify the key combinations of existing and new data sources that when combined with sophisticated real-time analytics, drive better decision making. This research therefore tries to understand how this double challenge can be managed.
CurrentTeaching: Foundation Course in Business Statistics with the CELE.
Research Supervisor/s: Kulwant Pawar
and Kim Tan
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