BIG DATA TECHNOLOGIES FOR E-BUSINESS– FUTURE OPPORTUNITIES, CHALLENGES AHEAD AND GROWING TRENDS

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Published: Apr 20, 2018
DOI: https://doi.org/10.26483/ijarcs.v9i2.5704
Keywords:
Big Data Analytics, Big data for E-Business, Analytics for E-Business, Big Data opportunities, Big Data Challenges

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Avinash BM
Harish Babu S

Abstract

E-Business today is considered as one of the most important and popular trends in business. E-Commerce, which is limited to online transactions i.e. buying and selling goods/services over internet, has a line of difference with E-Business that, in addition, covers all internet based communication and interactions with suppliers, manufacturers, logistics, and customers with the aim of improving business efficiency and process. To gain competitive edge over the peers in relation to costs, revenues and customer base, companies bring in robust technologies that can create formidable platform to achieve greater performance. One such breakthrough technology largely used is Big Data Analytics that can handle Volume, Velocity, Variety and Veracity of data that is generated in the real time. This research paper focuses on understanding the need for Big Data Analytics in E-Business companies, what opportunities can be harnessed by the use of it and the challenges that needs to be addressed.

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Vol. 9 No. 2 (2018): March-April 2018
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Articles

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References

Monica Bulger, Greg Taylor, Ralph Schroeder, Data-Driven Business Models: Challenges and Opportunities of Big Data, Oxford Internet Institute September 2014

Walunj Swapnil K. et.al, Big Data: Characteristics, Challenges and Data Mining, International Journal of Computer Applications (0975 – 8887), ICAIM – 2016

Amir Gandomi, Murtaza Haider, International Journal of Information Management Volume 35, Issue 2, April 2015, Pages 137 – 144

Akter, S., & Wamba, S.F. (2016). Big data analytics in e-Commerce: a systematic review and agenda for future research. Electron Markets, 26, 173- 194.

Minelli, M., Chambers, M., & Dhiraj, A. (2013). Business analytics (pp.99–125). Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today‟s Businesses.

Kang, K.-D., Son, S. H., & Stankovic, J. A. (2003). Differentiated real-time data services for E-commerce applications. Electronic Commerce Research, 3, 113–142.

Xindong Wu, , Xingquan Zhu, Gong-Qing Wu, Wei Ding, Data Mining with Big Data, IEEE Transactions On Knowledge And Data Engineering, Vol. 26, No. 1, January 2014

Rishabh Mishra et.al BIG DATA: OPPORTUNITIES AND CHALLENGES, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.6, June- 2015, pg. 27-35

EDPS, Meeting the challenges of big data, 19 November 2015

Tambe, P. (2014). Big Data Investment, Skills, and Firm Value. Management Science, 60(6): 1452-1469.

Beath, C., Becerra-Fernandez, I., Ross, J., & Short, J. (2012). Finding value in the information explosion. MIT Sloan Management Review, 53, 18–20.

Nguyễn Thị Thúy Hoà i, College of technology _ Danang University, BIG DATA – OPPORTUNITIES AND CHALLENGES, International Journal of Innovative Research in Technology & Science(IJIRTS), ISSN:2321-1156

Stephen Kaisler ; Frank Armour ; J. Alberto Espinosa ; William Money. Big Data: Issues and Challenges Moving Forward, 46th Hawaii International Conference on System Sciences (HICSS), 2013, ISSN :1530-1605

Zaharaddeen Karami Lawal et.al, A review: Issues and Challenges in Big Data from Analytic and Storage perspectives, International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume – 5 Issue -03 March, 2016 Page No. 15947-15961

K. S. Dr. Jangala., M. Sravanthi, K. Preethi and M. Anusha, "Recent Issues and Challenges on Big Data in Cloud computing," IJCST , , vol. Vol. 6, no. Issue 2, April - June 2015.

SUBHANKAR DHAR et.al, CHALLENGES AND BEST PRACTICES FOR ENTERPRISE ADOPTION OF BIG DATA TECHNOLOGIES, Journal of Information Technology Management Volume XXV, Number 4, ISSN#1042-1319, 2014

Christian, B., Boncz, P., Brodie, M.L., and Erling, O. 2011. “The Meaningful Use of Big Data: Four Perspectives – Four Challenges,†in Proceedings of the Twenty-five Semantic Web and Database researchers met at the 2011 STI Semantic Summit, Riga, Latvia.

Philip Russom, BIG DATA ANALYTICS, TDWI BEST PRACTICES

REPORT, FOURTH QUARTER 2011

Liebowitz, J. (2013). Big data and business analytics. Boca Raton: CRC Press.

Avinash B.M. et.al, Big Data Analytics for E-Commerce – Its Impact on Value Creation, International Journal of Advanced Research in Computer and Communication Engineering ISO 3297:2007 Certified Vol. 6, Issue 12, December 2017

Wei Fan, Albert Bifet. Mining big data: current status, and forecast to the future, ACM SIGKDD Explorations Newsletter, Volume 14 Issue 2, December 2012

Deepak S. Tamhane, Sultana N. Sayyad. Big Data Analysis Using Hace Theorem, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 4, Issue 1, January 2015

Kale Suvarna Vilas. Big Data Mining. International Journal of Computer Science and Management Research eETECME October 2013, ISSN 2278-733X

Weblinks:

www.easylearning.guru

www.wikibon.org

www.ibef.org

www.ibmbigdatahub.com

www.promptcloud.com

www.sssdecisions.com, top 5 Big Data Trends to look for in 2018, Mar 01 2018