Aybeniz S. Aliyeva

Work place: Institute of Information Technology of Azerbaijan National Academy of Sciences, B. Vahabzade str., Baku, AZ1141, Azerbaijan

E-mail: aybeniz63@rambler.ru

Website:

Research Interests: Computer systems and computational processes, Computational Learning Theory, Computer Architecture and Organization, Data Structures and Algorithms

Biography

Aybeniz Salman Aliyeva is a researcher, a senior researcher at the Institute of Information Technology of Azerbaijan National Academy of Sciences. Her research interests are Big Data technologies. She has published many papers in international journals and conferences.  

 

Author Articles
About Big Data Measurement Methodologies and Indicators

By Makrufa Sh. Hajirahimova Aybeniz S. Aliyeva

DOI: https://doi.org/10.5815/ijmecs.2017.10.01, Pub. Date: 8 Oct. 2017

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.

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