Modeling of an Efficient Low Cost, Tree based Data Service Quality Management for Mobile Operators using In-Memory Big Data Processing and Business Intelligence Use cases

EasyChair Preprint no. 682

Abstract

Abstract—Network Operators are shifting their business interest towards Data services in a geometric progression, as Data services is becoming the major source of Telco revenue. The wide use of Data platforms; such as WhatsApp, Skype, Hangout and other Over the Top (OTT) voice applications over the traditional voice services is a clear indication that Network Operators need to adjust their business model and needs. And couple with the adoption of Smartphones usage which grows continuously year by year, which means more subscribers to manage, large amount of transactions generated, more network resources to be added and evidently more human technical expertise required to ensure good service quality. With the large amount of transactions generated by data traffic and the high demanding service qualities, Mobile Network Operators are spending millions of rands/dollars to deploy Robust Service Quality Management (SQM) and Customer Experience Management (CEM) to stay competitive in the market. These solutions’ high cost is justified by the integration of Big Data Solutions, Machine Learning capabilities and good visualization of insight data. However, the Return on Investment (ROI) of the expensive systems are not as conspicuous as the provided functionalities and business rules. Therefore, in this paper an efficient model for low cost Service Quality Management system is presented, using the advantages of the In-Memory Big Data processing and simple low cost business Intelligence tools to showcase how a good Service Quality Management can be implemented with no big investment.

Keyphrases: Business Intelligence, Data Traffic and ROI., In-Memory Big Data, Over The Top Application (OTT), Service Quality Index, Service Quality Management

@Booklet{EasyChair:682,
  author = {Kingsley A. Ogudo and Dahj Muwawa Jean Nestor},
  title = {Modeling of an Efficient Low Cost, Tree based Data Service Quality Management for Mobile Operators using In-Memory Big Data Processing and  Business Intelligence Use cases},
  howpublished = {EasyChair Preprint no. 682},

  year = {EasyChair, 2018}}