Abstract
Globally industries, businesses, people, government are producing and consuming vast amounts of data on daily basis. Now-a-days, it’s become challenging to the IT world to deal with the variety and velocity of large volume of data. To overcome these bottlenecks, Big Data is taking a big role for catering data capturing, organizing and analyzing process in innovative and faster way. Big Data software and services foster organizational growth by generating values and ideas out of the voluminous, fast moving and heterogeneous data and by enabling completely a new innovative Information Technology (IT) eco-system that have not been possible before. The ideas and values are derived from the IT eco-system based on advanced data-analysis on top of the IT Servers, System Architecture or Network and Physical objects virtualization. In this research paper, authors have presented a conceptual framework for providing solution of the problem where required huge volume of data processing using different BIG data technology stack. The proposed model have given solution through data capturing, organizing data, analyzing data, finally making value and decision for the concern stakeholders.
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References
Akella, Janaki, Timo Kubach, Markus Löffler, and Uwe Schmid, Data-driven management: Bringing more science into management, McKinsey Technology Initiative Perspective, 2008.
Gartner Report on Big Data: August 2014.
Alan E. Webber, “B2B Customer Experience Priorities In an Economic Downturn: Key Customer Usability Initiatives In A Soft Economy,” Forrester Research, Inc., Feb. 19, 2008.
“Analytics: The real-world use of big data”, IBM Institute of Business Value, accessed Feb 11, 2012.
“Beyond the Hype of Big Data”, CIO.com, October 2011, accessed Feb 11, 2012.
“Retail 2020: Reinventing retailing–once again.” IBM and NewYork University Stern School of Business. January2012.
SAS 2013 Big Data Survey Research Brief, http://www.sas.com/resources/whitepaper/wp_58466.pdf.
Oracle Industries Scorecard http://www.oracle.com/us/industries/oracle-industries-scorecard-1692968.pdf.
Gleick, James, The information:A history.A theory.A flood (New York:Pantheon Books, 2011).
Schroeck, Michael, Rebecca Shockley, Dr. Janet Smart, Professor Dolores Romero-Morales and Professor Peter Tufano. IBM Institute for Business Value in collaboration with the Saïd Business School, University of Oxford. October 2012.
Kiron, David, Rebecca Shockley, Nina Kruschwitz, Glenn Finch and Dr. Michael Haydock. IBM Institute for Business Value in collaboration with MIT Sloan Management Review. October 2011.
IBM Analytic Tools http://www.ibm.com/marketplace/cloud/watson-analytics/us/en-us.
Splunk Big Data Tool http://www.splunk.com/en_us/products/splunk-enterprise.html.
Kyar Nyo Aye, Ni Lar Thein: A Comparison of Big Data Analytics Approaches Based on HadoopMapReduce, 2013.
Big Data Platform Comparisons http://www.informationweek.com/big-data/big-data-analytics/16-top-big-data-analytics-platforms/d/d-id/1113609?image_number=4.
Big Data Vendor Benchmark 2015 by Experton Group by Holm Landrock, Oliver Schonschek, Prof. Dr. Andreas Gadatsch.
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Sanyal, M.K., Bhadra, S.K., Das, S. (2016). A Conceptual Framework for Big Data Implementation to Handle Large Volume of Complex Data. In: Satapathy, S., Mandal, J., Udgata, S., Bhateja, V. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 433. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2755-7_47
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DOI: https://doi.org/10.1007/978-81-322-2755-7_47
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