KNOWLEDGE MANAGEMENT AND BIG DATA –DATA DRIVEN KNOWLEDGE BASE

Sri Vasavi College, Erode Self-Finance Wing 3rd February 2017 National Conference on Computer and Communication NCCC’17

Format: Volume 5, Issue 1, No 15, 2017

Copyright: All Rights Reserved ©2017

Year of Publication: 2017

Author: SARAVANAN PONNUSAMY,MS. T. PARIMALAM,

Reference:IJCS-228

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Abstract

Major issue with the business organizations is the unstructured data. This data is huge and normally spread across the organization in a different formats. In some occasions the data remains as just knowledge with some human resources. Managing all these different knowledge bases is becoming more challenge to the organizations. In order to safeguard the right knowledge, organizations spend lot of time and investment to build big data storage systems and knowledge base systems to read from there.The vast amounts of information can be collected, filtered and organized and be made available to those who need it in a format in which they need.Knowledge Management leads to the success of an organization. It is the management of knowledge built using the earlier experiences to reduce the rework involved so the cost, duration or both on re-production can be reduced. Also it helps to leverage the collective knowledge and experience of an organization to accelerate innovation and sharpen competitive advantage.In the recent times, many enterprises are investing in better Knowledge Management and Business Intelligence techniques in order to provide more value to their business. There are lot of techniques used by these organizations to analyze, create and utilize knowledge management data. As the data in available in several different forms, it is important to have multiple ways to deal with it.In this paper we will analyze the ways to build an effective knowledge management system from Big Data which can be used to effectively utilize an organization growth area.

References

1. Alavi, M., and Leidner, D. E. 2001. “Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues,” MIS Quarterly (25:1), pp. 107–136. 2.Assunção, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A. S., and Buyya, R. 2015. “Big Data computing and clouds: Trends and future directions,” Journal of Parallel and Distributed Computing: Special Issue on Scalable Systems for Big Data Management and Analytics (79–80), pp. 3. Begoli, E., and Horey, J. 2012. “Design principles for effective knowledge discovery from big data,” in Software Architecture (WICSA) and European Conference on Software Architecture (ECSA), 2012 joint working IEEE/IFIP conference on, M. Ali Babar, C. Cuesta, J. Savolainen, and T. Männistö, Helsinki, Finland, pp. 215–218. Bellenger, G. 2004. 4.“Creating Knowledge Objects,” (available athttp://www.systemsthinking.org/cko/guide.htm). Bellinger, G., Castro, D., and Mills, 2004.


Keywords

Knowledge Management, Business Intelligence.

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