About Big Data Measurement Methodologies and Indicators
Автор: Makrufa Sh. Hajirahimova, Aybeniz S. Aliyeva
Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs
Статья в выпуске: 10 vol.9, 2017 года.
Бесплатный доступ
The digitization of nearly all media and the increasing migration of social and economic activities to the İnternet, the development of social networking technologies, the İnternet of Things and cloud computing caused rapid increase in the volume of data and the formation of Big Data paradigm. Big Data involves technologies and tools for collecting, processing, analyzing and extracting useful knowledge from structured and unstructured data of large volumes generated at high speed by different sources. Increasing the volume, speed, diversity and value of Big Data began to play an important role in the creation of social relationships, competitive advantage and innovative fields. The development of the information society, the formation of digital economy, and the application Big Data technologies in different spheres of human activity required the quantitative and qualitative assessment of Big Data. In this article some approaches relate to the definition of Big Data have been reviewed. Methodological approaches and indicators for measuring Big Data have been researched. At the end, the indicators have been proposed for the measurement of factors that affected the growth and development of Big Data.
Big Data, Big Data indicators, Big Data measuremrnt, information infrastructure, innovation factors, technological factors, human factor
Короткий адрес: https://sciup.org/15015005
IDR: 15015005
Список литературы About Big Data Measurement Methodologies and Indicators
- The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things, 2014, https://www.emc.com/leadership/digital-universe/
- Big Data, Big Impact: New Possibilities for International Development, 2012, http://www.weforum.org/reports
- X. Jina, W Benjamin, X, Chenga, Y.Wanga, “Significance and Challenges of Big Data Research”, I.J. Big Data Research, vol. 2(2), pp. 59–64, 2015.
- Oxford Dictionaries: www.oxforddictionaries.com/definition//big-data, 2015.
- H. Hu, Y. Wen et al., “Toward Scalable Systems for Big Data Analytics”, IEEE Access Journal, vol. 2, 2014, pp. 652-689.
- P. Deep Kaur, A. Kaur and S. Kaur, "Performance Analysis in Bigdata", International Journal of Information Technology and Computer Science (IJITCS), 2015, vol.7, no.11, pp. 55-61. DOI: 10.5815/ijitcs.2015.11.07
- Gartner. IT Glossary Big Data, 2014, http://www.gartner.com/it-glossary/big-data/
- D. Boyd, K. Crawford, “Critical Questions for Big Data”, I.J. Information Communication & Society, vol.15, no.5, pp. 662-679, 2012.
- J. Gantz and D. Reinsel, “`Extracting value from chaos”, in Proc. IDC iView, 2011, pp. 1-12
- J. Manyika, M. Chui,,B. Brown et al., “Big Data: The Next Frontier for Innovation, Competition, and Productivity”, San Francisco, CA, USA: McKinsey Global Institute, 2011, pp. 1-137.
- M. Cooper, P. Mell, Tackling Big Data, 2012, http://csrc.nist.gov/groups/SMA/forum/documents/
- UN Global Pulse, “Big Data for Development: Challenges & Opportunities”, 2012, http://unglobalpulse.org
- UN Global Pulse, “Integrating Big Data into the Monitoring and Evaluation of Development Programmes”, 2016, http://unglobalpulse.org//
- M. Pospiech, C. Felden, “Towards A Big Data Theory Model”, Proceedings 2015, IEEE International conference on Big Data, 2015, pp. 2082-2090.
- P. Lyman, and Hal R. Varian, "How Much Information", 2003. http://groups.ischool.berkeley.edu/
- J. Gantz et. al., The Diverse and Exploding Digital Universe: An Updated Forecast of Worldwide Information Growth Through 2011, IDC White Paper, March 2008.
- R. Westervelt IDC White Paper: Information-Centric Security: Why Data Protection Is the Cornerstone of Modern Enterprise Security Programs, March 2017, symantec.com›content/dam/
- M. Hilbert, H. Lopez,”The World’s Technological Capacity to Store, Communicate, and Compute”, Information. Science, 2011, vol.332(6025), pp. 60 –65.
- Cisco Visual Networking Index: Forecast and Methodology, 2016–2021, http://www.cisco.com
- R. Bohn, J. Short, “How much information? 2009 report on American consumers, Global Information Industry Center of University of California, 2009, http://hmi.ucsd.edu/howmuchinfo.php
- 2014 The Massachusetts Big Data Report: A Foundation for Global Leadership, http://www.masstech.org/sites/mtc/files/documents/Full-Report-2014-Mass-Big-Data-Report.pdf
- Massachusetts Big Data Indicators 2015, http://massbigdata.org/assets/Uploads/Final-Big-Data-Report-2015.pdf
- G. Catteneo, “The European Data Market”, NESSI summit in Brussels on 27 May 2014, http://www.nessi-europe.eu/
- Final results of the European Data Market study measuring the size and trends of the EU data economy, 2017, https://ec.europa.eu/digital-single-market/en/news/
- G. Halevi, The Evolution of Big Data as a Research and Scientific Topic Overview of the Literature, Research Trends, Issue 30, 2012, https://www.researchtrends.com/wp-content/
- M. Hajirahimova, A. Aliyeva, “Some indicators of Big Data”, IOSR Journal of Engineering (IOSRJEN), 2016, vol. 06, Issue 10,pp. 01-06
- R. M. Aliguliyev, M. Sh. Hajirahimova, A. S. Aliyeva, “Current scientific and theoretical problems of Big Data”, Problems of information society, 2016, №2, 34–45.
- L. Cai, Y. Zhu, “The Challenges of Data Quality and Data Quality Assessment in the Big Data Era”, Data Science Journal. 2015, vol.14, p.2.
- M. Hilbert, “How to Measure “How Much Information”? Theoretical, Methodological, and Statistical Challenges for the Social Sciences”, International Journal of Communication, 2012, vol.6., pp.1042–1055
- N.V Korytnikova,. “Online Big Data as a source of analytic information in online research", Sotsiologicheskie Issledovaniya, 2015, Issue 8, pp. 14-24.
- Big Data for Measuring the Information Society, 2016, http://www.itu.int/net4/ITU-D/CDS/projects/display.asp?ProjectNo=2GLO16081
- OECD, “Exploring data-driven innovation as a new source of growth: Mapping the policy issues raised by “big data”, Supporting Investment in Knowledge Capital, Growth and Innovation, OECD Publishing, 2013, DOI:http://dx.doi.org/10.1787/9789264193307-12-en
- Internet of Things to generate 400 zettabytes of data by 2018, v3.co.uk
- The Zettabytes Era: Trends and Analysis, 2017, www.cisco.com
- Inside Ten of the World’s Largest Data Centers, 2010, http://wikibon.org/blog/inside-ten-of-the-worlds-largest-data-centers/
- B. Jena, M. Kumar Gourisaria, S. Swarup Rautaray, M.Pandey,"A Survey Work on Optimization Techniques Utilizing Map Reduce Framework in Hadoop Cluster", International Journal of Intelligent Systems and Applications (IJISA), vol.9, no.4, pp.61-68, 2017. DOI: 10.5815/ijisa.2017.04.07
- M. Abdrabo, M. Elmogy, G. Eltaweel, Sh. Barakat, “Enhancing Big Data Value Using Knowledge Discovery Techniques”, I.J. Information Technology and Computer Science, 2016, vol.8, pp. 1-12, http://www.mecs-press.org/, DOI: 10.5815/ijitcs.2016.08.01
