Edited By Sevinc Gülseçen, Zerrin Ayvaz Reis, Murat Gezer and Çiğdem Erol
Nowadays, an end-to-end industrial transformation called Industry 4.0 sets new goals for manufacturing and impacts on business outcomes. With some of its characteristic elements such as IoT (Internet of Things), digital twin simulation models, advanced robots, big data analytics, and virtual/augmented reality, Industry 4.0 is «de facto» going further. The book aims to provide relevant theoretical frameworks and the latest empirical research findings in the area of Management Information Systems (MIS) with the scope of Industry 4.0. The strategic role of Industry 4.0 in the distributed business environment and the necessity to protect and properly utilize its key elements at different levels of organizations as well as in society are discussed.
Big Data on Cloud for Telecommunications Industry (Abdulkadir Hızıroğlu / Dilan Özcan Kalfa / Ourania)
← 318 | 319 →
Abdulkadir Hızıroğlu, Dilan Özcan Kalfa*, Ourania Areta and Musab Talha Akpınar
Big Data on Cloud for Telecommunications Industry
Business analytics refers to applying various analytics techniques to data that may be generated through the internal business processes, the operational data stores or could be acquired through external and open data sources (Gandomi & Haiza, 2015). These data sources can be in structured or semi/unstructured form. Considering the fact that huge amount of data has been generated by businesses, especially by service industries, the problem that needs to be tackled is to handle such a big corporate asset (aka big data) and to utilize them in line with the strategic focus of the organizations in order to extract valuable knowledge.
Big data could be defined as the massive data sets. In these data sets, the term “big” depends also on the complex context inside. The term “big” is also referring to the very large size. For this reason, most of the big data sets are hard to fit into the computer’s memory in one execution time. The big size depends on the content source(s) of the data. These content sources are created from three main sources. One of the main sources is traditional enterprise data in which it is basically created and managed by the standard SQL structure transactions. CRM systems, transactional ERP data and similar enterprise and transaction-oriented system could be...
You are not authenticated to view the full text of this chapter or article.
This site requires a subscription or purchase to access the full text of books or journals.
Do you have any questions? Contact us.Or login to access all content.