CHAPTER ONE

1.0      INTRODUCTION

1.1   BACKGROUND OF STUDY

Big data broadly refers to the new methods and technologies for collecting, managing, and analyzing in real time the vast amount of both structured and unstructured data. Although telcos have been moving multiple terabytes of data around their networks for years, today's networks have seen unprecedented changes in term volumes of data moved including video, variety comprising the social networking data, and complexity of that data that is not necessarily structured.

A recent report by Research and Markets (2014) on global market in telecom industry discovered that the telecom sector's use of data analytics tools is expected to grow at a compound annual growth rate of 28.28 percent over the next four years. With the telecommunications companies controlling the infrastructure through which data flows, they have more data than any other industry on where their customers are, how they interact, and how they transact business. By using data acquisition and analytics technologies, this massive amount of data can be used to gain more consumer insight and hence enhance customer experience. Mobile data traffic is expected to grow by approximately 60 percent year over year through 2016, driven mainly by video. (Source: Ericsson Traffic and Market Data Report, November 2011.)

The telecom industry is facing an unprecedented amount of data, fluxing in at a speed never seen before. Analysis of petabyte-scale and streaming data was challenging before, if not impossible, because the costs of the hardware and software needed to handle the data were prohibitive. Further, since the return of data analytics investment is sometimes hard to measure (e.g., customer royalty) or take a long time to materialize, large spending was usually discouraged.

Today, the trend of using open source and commodity Hardware in big data platform has lessen the above concern to a certain degree. Many open sources have either a free community version or an enterprise version with moderate service/license fee.

The Apache projects Elmi, E.H.; (2012) are one of the most prominent examples.

Telecommunication system in the following terms: “Telecommunication” occurs when the exchange of information between two entities (communication) includes the use of technology Vincent PH (1988). Communication technology uses channels to transmit information (as electrical signals), either over a physical medium (such as signal cables), or in the form of electromagnetic waves”.

Poor’s definition of a telecommunication system brings out very clearly its intimate relationship to statistics: “Signal detection and estimation is the area of study that deals with the processing of information-bearing signals for the purpose of extracting information from there. Applications of the theory of signal detection and estimation are found in many areas, such as communications and automatic control”.

1.2   STATEMENT OF THE PROBLEM

Big data does not store data by itself, does not generate business value, and this is true of traditional databases, data warehouses, and the new technologies such as Hadoop for storing big data. Though the issue with big data could be that there are no technical or trained hands to manage it and also operate. Finally, several researches have been carried out on the telecommunications but not even a single research has been carried out on the impact of big data analytics on telecommunications.

1.3   AIMS AND OBJECTIVES OF STUDY

         The main aim of the study is to determine the impact of big data analytics on telecommunication. Other specific objectives of the study include:

1.          to determine the effect of big data analytics on telecommunications.

2.          to determine the factors affecting big data analytics.

3.          to determine the extent to which big data analytics affects telecommunications.

4.          to proffer possible solutions to the problems.

1.4   RESEARCH QUESTIONS

1.          What is the effect of big data analytics on telecommunication?

2.          What are the factors affecting big data analytics?

3.          What is the extent to which big data analytics affects telecommunications?

4.          What are the possible solutions to the problems?

1.5   SIGNIFICANCE OF STUDY

The study on the impact of big data analytics on telecommunications will be of immense benefit to the entire telecommunication centers in the country in the sense that it will enable them to make available network as well as good internet accessibility to avoid inconveniencies by the users. It will also enable them to look out for smart and dedicated staff at the place of service in other to avoid unnecessary complaints from the end-users. Finally, the study will contribute to the body of existing literature and knowledge to this field of study and basis for further research.

1.6   SCOPE OF STUDY

The study on the impact of big data analytics is limited to telecommunications.

1.7   LIMITATION OF STUDY

Financial constraint- Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet, questionnaire and interview).

Time constraint- The researcher will simultaneously engage in this study with other academic work. This consequently will cut down on the time devoted for the research work.

1.8   DEFINITION OF TERMS

ImpactA marked effect or influence.

Big DataBig data is a term used to refer to the study and applications of data sets that are too complex for traditional data-processing application software to adequately deal with.

Analytics This is the discovery, interpretation, and communication of meaningful patterns in data.

Telecommunications      Is the transmission of signs, signals, messages, words, writings, images and sounds or information of any nature by wire, radio, optical or electromagnetic systems.

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