Big Data: Concept, Potentialities and Vulnerabilities

Fernando Almeida


The evolution of information systems and the growth in the use of the Internet and social networks has caused an explosion in the amount of available data relevant to the activities of the companies. Therefore, the treatment of these available data is vital to support operational, tactical and strategic decisions. This paper aims to present the concept of big data and the main technologies that support the analysis of large data volumes. The potential of big data is explored considering nine sectors of activity, such as financial, retail, healthcare, transports, agriculture, energy, manufacturing, public, and media and entertainment. In addition, the main current opportunities, vulnerabilities and privacy challenges of big data are discussed. It was possible to conclude that despite the potential for using the big data to grow in the previously identified areas, there are still some challenges that need to be considered and mitigated, namely the privacy of information, the existence of qualified human resources to work with Big Data and the promotion of a data-driven organizational culture.


Big Data; Distributed Computing; Data Analysis; Predictive Analytics; Hadoop.


R. Sharda, D. Delen, and E. Turban, Business Intelligence, Analytics, and Data Science: A Managerial Perspective. Pearson Education, 2017. ISBN: 978-0134633282.

O. Ylojoki, and J. Porras, “Perspectives to Definition of Big Data: A Mapping Study and Discussion”, Journal of Innovation Management, vol. 4, no. 1, pp. 69-91, 2016.

R. Kune, P. Konugurthi, A. Agarwal, R. Chillarige, and R. Buyya, “The Anatomy of Big Data Computing”, Journal Software – Practice & Experience, vol. 46, no. 1, pp. 79-105, 2016. doi: 10.1002/spe.2374.

I. Lee, “Big Data: Dimensions, Evolution, Impacts, and Challenges”, Business Horizons, vol. 60, no. 3, pp. 293-303, 2017. doi: 10.1016/j.bushor.2017.01.004.

C. Yang., Q. Huang, Z. Li, K. Liu, and F. Hu, “Big Data and cloud computing: innovation opportunities and challenges”, International Journal of Digital Earth, vol. 10, no. 1, pp. 13-53, 2017. doi: 10.1080/17538947.2016.1239771.

U. Sivarajah, M. Kamal, Z. Irani, and V. Weerakkody, “Critical analysis of Big Data challenges and analytical methods”, Journal of Business Research, vol. 70, pp. 263-286, 2017. doi: 10.1016/j.jbusres.2016.08.001.

S. Owais, and N. Hussein, “Extract Five Categories CPIVW from the 9V’s Characteristics of the Big Data”, International Journal of Advanced Computer Science and Applications, vol. 7, no. 3, pp. 254-258, 2016.

H. Bhosale, and D. Gadekar, “A Review Paper on Big Data and Hadoop”, International Journal of Scientific and Research Publications, vol. 4, no. 10, pp. 1-7, 2014.

B. Sahare, A. Naik, and K. Patel, “Study of Hadoop”, International Journal of Computer Science Trends and Technology (IJCST), vol. 2, no. 6, pp. 40-43, 2014.

V. Pellakuri, and R. Rao, “Hadoop Mapreduce Framework in Big Data Analytics”, International Journal of Computer Trends and Technology (IJCTT), vol. 8, no. 3, pp. 115-119, 2014. doi: 10.14445/22312803/IJCTT-V8P121.

TutorialsPoint, Hadoop Tutorial, available at

P. Dave, Big Data – Buzz Words: What is MapReduce, 2013, available at

F. Sarrocco, V. Morabito, and G. Meyer, Exploring the Next Generation Financial Services: The Big Data Revolution, 2016, available at

S. Erickson, and H. Rothberg, “Intangible dynamics in financial services”, Journal of Service Theory and Practice, vol. 26, no. 5, pp. 642-656, 2016. doi: 10.1108/JSTP-04-2015-0093.

X. Tian, R. Han, L. Wang, G. Lu, and J. Zhan, “Latency critical big data computing in finance”, The Journal of Finance and Data Science, vol. 1, no. 1, pp. 33-41, 2015. doi: 10.1016/j.jfds.2015.07.002.

R. Shockley, and K. Mercier, Analytics: The Real-World Use of Big Data in Retail, 2017, available at

J. Aloysius, H. Hoehle, and V. Venkatesh, “Exploiting big data for customer and retailer benefits”, International Journal of Operations & Production Management, vol. 36, no. 4, pp. 467-486, 2016. doi: 10.1108/IJOPM-03-2015-0147.

D. Grewal, A. Roggeveen, and J. Nordfalt, “The Future of Retailing”, Journal of Retailing, vol. 93, no. 1, pp. 1-6, 2017. doi: 10.1016/j.jretai.2016.12.008.

J. Wu, H. Li, S. Cheng, and Z. Lin, “The Promising Future of Healthcare Services: When Big Data Analytics Meets Wearable Technology”, Information & Management, vol. 53, no. 8, pp. 1020-1033, 2016. doi: 10.1016/

D. Dimitrov, “Medical Internet of Things and Big Data in Healthcare”, Healthcare Informatics Research, vol. 22, no.3, pp. 156-163, 2016. doi: 10.4258/hir.2016.22.3.156.

C. Kruse, R. Goswamy, Y. Raval, and S. Marawi, “Challenges and Opportunities of Big Data in Health Care: A Systematic Review”, JMIR Medical Informatics, vol. 4, no. 4, 2016. doi: 10.2196/medinform.5359.

K. Abouelmehdi, A. Beni-Hssane, H. Khaloufi, and M. Saadi, “Big Data security and privacy in healthcare: a review”, Procedia Computer Science, vol. 113, pp. 73-80, 2017. doi: 10.1016/j.procs.2017.08.292.

K. Abouelmehdi, A. Beni-Hssane, and H. Khaloufi, “Big healthcare data: preserving security and privacy”, Journal of Big Data, vol. 5, no. 1, pp. 1-18, 2018. doi: 10.1186/s40537-017-0110-7.

D. Kochhar, Big Data in Public Transportation, 2016, available at

R. Kanniyappan, and B. McQueen, What’s the Big Deal about Big Data in Transportation?, 2014, available at

S. Wolfert, L. Ge, C. Verdouw, and M. Bogaardt, “Big Data in Smart Farming”, Agricultural Systems, vol. 153, pp. 69-80, 2017. doi: 10.1016/j.agsy.2017.01.023.

K. Bronson, and I. Knezevic, “Big Data in Food and Agriculture”, Big Data & Society, vol. 3, no. 1, pp. 1-5, 2016. doi: 10.1177/2053951716648174.

K. Porter, Big Data in Energy: Big Opportunities and Big Risks, 2017, available at

H. Dakl, A. El Hannani, A. Aqqal, A. Haidine, and A. Dahbi, “Big Data management in smart grid: concepts, requirements and implementation”, Journal of Big Data, vol. 4, no. 13, pp. 1-19, 2017. doi: 10.1186/s40537-017-0070-y.

N. Koseleva, and G. Ropaite, “Big Data in Building Energy Efficiency: Understanding of Big Data and Main Challenges”, Procedia Engineering, vol. 172, pp. 544-549, 2017. doi: 10.1016/j.proeng.2017.02.064.

V. Agrawal, The Impact of Big Data and Analytics on Manufacturing, 2016, available at

R. Delgado, Big Data’s Transformation of the Manufacturing Industry, 2017, available at

K. Nagorny, Lima-Monteiro, P., J. Barata, A. Colombo, “Big Data Analysis in Smart Manufacturing: A Review”, International Journal of Communications, Network and System Sciences, vol. 10, no. 3, pp. 31-58, 2017. doi: 10.4236/ijcns.2017.103003.

F. Tao, Q. Qi, A., Liu, and A. Kusiak, “Data-driven smart manufacturing”, Journal of Manufacturing Systems, 2018. doi: 10.1016/j.jmsy.2018.01.006.

K. Witkowski, “Internet of Things, Big Data, Industry 4.0 – Innovative Solutions in Logistics and Supply Chains Management”, Procedia Engineering, vol. 182, pp. 763-769, 2017. doi: 10.1016/j.proeng.2017.03.197.

H. Lippell, “Big Data in the Media and Entertainment Sectors”, in J. Cavanillas, E. Curry, and W. Wahlster (eds.) New Horizons for a Data-Driven Economy, Springer, 2016. ISBN: 978-3-319-21569-3.

S. Philips, 5 Ways Big Data Plays as a Major Role in the Media and Entertainment Industry, 2017, available at

R. Munné, “Big Data in the Public Sector”, in J. Cavanillas, E. Curry, and W. Wahlster (eds.) New Horizons for a Data-Driven Economy, Springer, 2016. doi: 10.1007/978-3-319-21569-3.

S. Lauchlan, Government’s Big Data Dilemma – Building Public Trust During a Data Science Skills Crisis, 2017, available at

J. Moreno, M. Serrano, and E. Fernández-Medina, “Main Issues in Big Data Security”, Future Internet, vol. 8, no. 44, pp. 1-16, 2016. doi: 10.3390/fi8030044.

D. Hu, D. Chen, Y. Zhang, and S. Pei, “Research on Hadoop Identity Authentication Based on Improved Kerberos Protocol”, International Journal of Security and its Applications, vol. 9, no. 11, pp. 429-438, 2015. doi: 10.14257/ijsia.2015.9.11.39.

A. Pentland, With Big Data Comes Big Responsibility, 2014, available at

A. Lambshead, “The Importance of Standards in a Time of Innovation”, SMPTE Motion Imaging Journal, vol. 123, no. 8, pp. 7-7, 2014. doi: 10.5594/j18480.

C. Tsai, “Big data analytics: a survey”, Journal of Big Data, vol. 2, no. 1, pp. 1-32, 2015. doi: 10.1186/s40537-015-0030-3.

C. Maple, “Security and privacy in the internet of things”, Journal of Cyber Policy, vol. 2, no. 2, pp. 155-184, 2017. doi: 10.1080/23738871.2017.1366536.

V. Brock, and H. Khan, “Big data analytics: does organizational factor matters impact technology acceptance?”, Journal of Big Data, vol. 4, no. 21, pp. 1-28, 2017. doi: 10.1186/s40537-017-0081-8.

M. Bendre, and V. Thool, “Analytics, challenges and applications in big data environment: a survey”, Journal of Management Analytics, vol. 3, no. 3, pp. 206-239, 2016. doi: 10.1080/23270012.2016.1186578.

B. Balachandran, and S. Prasad, “Challenges and Benefits of Deploying Big Data Analytics in the Cloud for Business Intelligence”, Procedia Computer Science, vol. 112, pp. 1112-1122, 2017. doi: 10.1016/j.procs.2017.08.138.

S. Singh, I. Chana, and M. Singh, “The Journey of QoS-Aware Autonomic Cloud Computing”, IT Professional, vol. 19, no. 2, pp. 42-49, 2017. doi: 10.1109/MITP.2017.26.

P. Jain, M. Gyanchandani, and N. Khare, “Big data privacy: a technological perspective and review”, Journal of Big Data, vol. 3, no. 25, pp. 1-25, 2016. doi: 10.1186/s40537-016-0059-y.

A. Auld, The big problem in big data: a lack of skills, 2017, available at

Full Text: PDF

DOI: 10.28991/esj-2018-01123


  • There are currently no refbacks.

Copyright (c) 2018 Fernando Almeida