Iqbal, Muhammad and Alam Kazmi, Syed Hasnain and Manzoor, Dr. Amir and Rehman Soomrani, Dr. Abdul and Butt, Shujaat Hussain and Shaikh, Khurram Adeel (2018): A Study of Big Data for Business Growth in SMEs: Opportunities & Challenges. Published in: International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) , Vol. 1, No. 1 (March 2018): pp. 1-7.
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Abstract
In today's world the data is considered as an extremely valued asset and its volume is increasing exponentially every day. This voluminous data is also known as Big Data. The Big Data can be described by 3Vs: the extreme Volume of data, the wide Variety of data types, and the Velocity required processing the data. Business companies across the globe, from multinationals to small and medium enterprises (SMEs), are discovering avenues to use this data for their business growth. In order to bring significant change in businesses growth the use of Big Data is foremost important. Nowadays, mostly business organization, small or big, wishes valuable and accurate information in decision-making process. Big data can help SMEs to anticipate their target audience and customer preferences and needs. Simply, there is a dire necessity for SMEs to seriously consider big data adoption. This study focusses on SMEs due to the fact that SMEs are backbone of any economy and have ability and flexibility for quicker adaptation to changes towards productivity. The big data holds different contentious issues such as; suitable computing infrastructure for storage, processing and producing functional information from it, and security and privacy issues. The objective of this study is to survey the main potentials & threats to Big Data and propose the best practices of Big Data usage in SMEs to improve their business process.
Item Type: | MPRA Paper |
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Original Title: | A Study of Big Data for Business Growth in SMEs: Opportunities & Challenges |
Language: | English |
Keywords: | SME; Big Data; Efficieny; Analytics; Competitive Advantage |
Subjects: | C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs M - Business Administration and Business Economics ; Marketing ; Accounting ; Personnel Economics > M1 - Business Administration M - Business Administration and Business Economics ; Marketing ; Accounting ; Personnel Economics > M1 - Business Administration > M15 - IT Management |
Item ID: | 96034 |
Depositing User: | Syed Hasnain Alam Kazmi |
Date Deposited: | 18 Sep 2019 15:52 |
Last Modified: | 26 Sep 2019 13:10 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/96034 |