Leveraging cloud based big data analytics in knowledge management for enhanced decision making in organizations

نویسنده

  • Mohammad Shorfuzzaman
چکیده

In recent past, big data opportunities have gained much momentum to enhance knowledge management in organizations. However, big data due to its various properties like high volume, variety, and velocity can no longer be effectively stored and analyzed with traditional data management techniques to generate values for knowledge development. Hence, new technologies and architectures are required to store and analyze this big data through advanced data analytics and in turn generate vital real-time knowledge for effective decision making by organizations. More specifically, it is necessary to have a single infrastructure which provides common functionality of knowledge management, and flexible enough to handle different types of big data and big data analysis tasks. Cloud computing infrastructures capable of storing and processing large volume of data can be used for efficient big data processing because it minimizes the initial cost for the large-scale computing infrastructure demanded by big data analytics. This paper aims to explore the impact of big data analytics on knowledge management and proposes a cloud-based conceptual framework that can analyze big data in real time to facilitate enhanced decision making intended for competitive advantage. Thus, this framework will pave the way for organizations to explore the relationship between big data analytics and knowledge management which are mostly deemed as two distinct entities.

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عنوان ژورنال:
  • CoRR

دوره abs/1702.04474  شماره 

صفحات  -

تاریخ انتشار 2017