Leveraging cloud based big data analytics in knowledge management for enhanced decision making in organizations
📝 Abstract
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.
💡 Analysis
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.
📄 Content
International Journal of Distributed and Parallel Systems (IJDPS) Vol.8, No.1, January 2017 DOI:10.5121/ijdps.2017.8101 1
LEVERAGING CLOUD BASED BIG DATA ANALYTICS IN KNOWLEDGE MANAGEMENT FOR ENHANCED DECISION MAKING IN ORGANIZATIONS
Mohammad Shorfuzzaman Department of Computer Science, Taif University, Taif, Saudi Arabia
ABSTRACT
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.
KEYWORDS
Knowledge management, cloud computing, big data, data analytics, competitive advantage, decision making.
- INTRODUCTION
Knowledge management (KM) is increasingly becoming crucial for enhanced decision making in organizations. Hence, organizations are exploring ways to effectively accumulate and deal with the data, information and knowledge that are accessible today. The earlier development of KM was facilitated by the use of the Information and communications technology (ICT) in late eighties. The goal was to manage the increasing amount of data, information and to ensure its usage and flow across the organization. In the next stage, two pioneers of KM [2] proposed the social, cognitive and business aspects of KM and regarded knowledge as an intellectual asset that an organization should construct and monitor. The size of data and information that are handy today is much more than what we could possibly envisage a decade ago. There is a pressing need to investigate such big amount of data and establish its relationship with KM to enhance organizational decision making and acquire competitive advantage.
The emergence of big data as described by the authors in [24] is due to the drastic increase of processing power, the availability of data with high volume, velocity and variety, and the combination of customary data management and open-sourced technologies and commodity hardware. With the explosion of the Internet, mobile devices, and social media, the impact of big data became apparent in numerous areas and industries. The competence of organizations to make International Journal of Distributed and Parallel Systems (IJDPS) Vol.8, No.1, January 2017 2 use of big data to derive actionable insights has appeared as a vital policy to build competitive advantages.
This 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 [4, 5, 6]. New technologies and architectures are required to store and analyze this data and in turn generate vital real-time information for decision making in organizations. This has opened the door for the researchers to focus on big data analytics which are likely to play a radical role in the success of organizations. The challenge is to collect, store, and analyze the enterprise big data at the right speed from sources such as sales, supply chain, research, and customer relations to build the knowledge base for effective decision making of the organizations. Recent studies also revealed the fact that the utilization of big data has augmented notably in decision-making [3] and both public and private organizations are reaping benefits from this emerging technology [1].
Thus, with the increasingly large amount of data, it is necessary to have a single infrastructure which provides common functionality of big data management, and flexible enough to handle different types of big data and big d
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