There was need for technology that can readily store analyze and process petabyte sized data without depending on massive investments in enterprise hardware and storage for data warehousing as it currently obtains for telecommunication operators Respite for this challenge is being provided by the open source technologies driving big data analytics providing the capability for usage of thousands of commodity servers for parallel processing of huge data on the telecommunication operators network while being computation to the data The architecture of this technology which revolves around the Apache Hadoop framework and the architecture of how it can be properly deployed to optimally handle the big data analytics need of the telecommunications operator in comparison with the current conventional relational database management systems RDBMS and how this will contribute an edge to the telecommunication operators is researched in this report Chapter on of this thesis is the Introduction of the thesis It provides an introduction into big data analytics as well as background into the research It also clearly states what the problems statement for the thesis is and as well states the contribution of the thesis The chapter two details the review of literature on big data analytics techniques and also the sources and trends of big data telecommunication industry It also dives into the conventional existing and also the emerging new technologies in big data analytics as well as the applications of these new technologies
With current advances of telecommunication technology and ever increasing mobile technology cellular networks have turned out to be each huge generator and host of big data Liu Liu and Ansari 2014 During the geolocation of mobile gadgets recording smartphone calls and recording activities of mobile applications a sizable volume of data is generated and sustained on the operators networks In time past this huge data on the mobile operators networks weren't given much attention and sometimes discarded With the accumulation of huge data consistently on the mobile operators network and consequent upon the quick evolution of big data analytics the outstanding benefit and value hidden in the huge data is now been revealed It s of huge benefits to utilize the insights from these data to enhance and optimize the overall performance of operators cellular networks as well as maximize operators revenue Bi et al 2015
Conventional data analytic using RDBMS Relational Database Management Systems had revealed its inadequacy in handling big data on the cellular operators network Firstly conventional data analytic handles analysis and processing of well structured data only Ironically the massive amount of system application primarily based data output however is typically unstructured Secondly data analysis implementation is historically done within a department in the organization or an enterprise unit after which analytical conclusions are derived from very restricted angles or in silos instead of from a larger global perspectives Thirdly the analytics in particular narrows and focuses on transaction data mostly whereby less emphasis and effort is paid to operational data as a result of its inadequacy in making a real time selections
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