Comparison of Telecommunication Organizations

Concept Of Big Data

It is a term which is very broad in nature, used to represent data or information sets that may be highly complicated or very large (Chen, Alspaugh and Katz, 2012). Currently, it is one of the leading aspects of working for companies in different industries, as they have become extensively dependent on it. Various studies and experts of numerous sectors opine that, organizations nowadays heavily rely upon the Big Data, as they perceive it as a source of obtaining intensive knowledge about their area of operations and also demands of target customers. Basically, big data is related to large amount of data that may be structured, semi-structured or even unstructured and has the potential to be analysed intensively for purposes of extracting varied kinds of information from it (Jeon, 2012). Data in such situations is not calculated in gigabytes or terabytes, instead it is measured in petabytes or exabytes. It includes data sets which may range in between sizes that could be well beyond the comprehension and use by traditional software tools to capture, manage and process data within a tolerable time frame. As the name suggests, 'Big Data' is used to denote voluminous amount of data, which cannot be calibrated with normal or day-to-day software for recording and collating them. Modern day companies are now using big data as a technique through which extensive and highly detailed information about target markets can be obtained; and then used to formulate relevant business strategies and plans (Debnath and Shankar, 2008).

Impact Of Big Data Over Network Infrastructure

It is a well known fact that, big data is one of the most hyped phenomenons of the IT industry and a very useful tool for companies across various sectors with the help of which they can carry out their business functions in an efficient and effective manner. Through the use of big data, managing operations of company can become a lot simpler for its management; in addition to the fact that they can develop useful strategies (Stanley, 2013). For telecommunication companies, emergence of big data has changed the way they used to develop and manage their infrastructural resources; along with using them in the most effective of manner. In the following paragraphs, an assessment has been made into impact of big data over network infrastructure for two telecommunication companies – EE Limited and Southern Business Technologies.

EE Limited

Formerly known as Everything Everywhere (EE), is a British network operator and was formed as a 50:50 joint venture between Deutsche Telekom and Orange S.A. It provides mobile networks and internet services to different customers, indicating that the firm operates in a customer based market (Townsend, 2013). If the company starts to use big data and makes it a regular part of business functions, then its management would have to bring about radical changes in its network infrastructure. This is because of reason that, different kinds of servers  would collect and assimilate information of large quantities. Considering the highly competitive nature of this industry, it can be said that it would be imperative for management at EE Limited to implement changes in its network infrastructure, so that, techniques and software associated with big data can be used in an efficient and effective manner. In this sense, one of the prime impacts of using this tool would be related to gaining access to new servers and installing them in the company, along with connecting them with different computer systems in the firm (Mu and Lee, 2005). To do the same management, the organization would have to contact with different suppliers or vendors who could provide firm with information about different servers that may make the task of obtaining and managing big data effectively. There are various kinds of servers and hardware that can be used by the company in this regard. For instance, management of EE Limited would have to identify the bandwidth of their operations and then understand if there is any need to change the same. Bringing about a change in bandwidth of operations of the company would allow management to determine ways in which they can procure large amounts of information about target market (Berkhout and Duin, 2007). Through such an approach not only the process of collecting such data sets would become a lot simpler, but also the system through which this information are evaluated on various parameters can be determined easily and effectively.

There are various kinds of servers and hardware that can be used by the company in this regard. For instance, management of EE Limited would have to identify the bandwidth of their operations and then understand if there is any need to change the same. Bringing about a change in bandwidth of operations of the company would allow management to determine ways in which they can procure large amounts of information about target market (Veeramani, 2014). Through such an approach not only the process of collecting such data sets would become a lot simpler, but also the system through which these information are evaluated on various parameters can be determined easily and effectively. It has been observed that many organizations such as EE Limited still operate on 1 GbE bandwidth, due to which their operational processes are a lot slower in speed than that of other organizations operated in customer based telecommunications industry (Nuechterlein and Weiser, 2005). Further, this also means that the company will have to increase its expenditures by a great margin. This is mainly because of reason that firm would have to obtain permission for increasing the bandwidth along with fulfilling different latency requirements for the same. Thus, it can be said that if management at EE Limited decides to use big data on a regular basis and make it an integral part of business functioning, then authorities will have to increase the bandwidth so that load of big data can be handled easily and effectively (Davenport, 2014). For the same, new servers will have to be bought by the firm. This is the prime impact of big data over network infrastructure for the company and would prove to be of great use to the company, primarily because of reason that it would enhance capabilities of EE Limited to utilize concepts of big data and make it a crucial part of business operations of the firm.

Southern Business Technologies

SBT (Southern Business Technologies) is a business telecommunications provider based out of South England and also one of the premier names in the given industry. Since the 90s, this company has grown by leaps and bounds, due to which it has become one of the largest independent supplier of communication equipments and services (Kleyman, 2014). It has been observed that present IT based architecture of the networks used by the company aims at providing customers with an ability to contact the firm with any of their grievance or issue and report it during 9 am to 5 pm through Monday to Friday. But it has been recommended to the firm that it should develop a system through which customers can report issued faced by them on 24*7 basis, i.e. at any time during the whole week. For the same, management would have to keep a thorough record of their customers and issues that they have suffered from in the past. Stallings (2007) recalls that for developing such systems, tools of big data can be very helpful to the organization. In this regard, it can be said that if SBT aims at using the said concept, then its networking infrastructure would have to be changed by great margins (Provost and Fawcett, 2013). It can be supported through fact that a fabric based architecture would have to be developed by management of company in this regard. Using this given system will allow authorities to make a link or connection between all its servers, with the help of which effective telecommunication services can be provided to corporate customers of company (Buhl, 2013). This way their experience and association with the company will improve by great margins. Since it is more 'east-west' or 'server-server' based model, it would become a lot easier for SBT to gather and compile information about its customers and determine the best ways through which maximum satisfaction can be provided to the customers.

Further, using big data would enable the company to increase its traffic capacity through which performance and quality of the existing networks would enhance by great margins. It can be supported through fact that installing high capacity servers and systems or techniques of managing big data would enable it to attract large amounts of traffic, i.e. gain the ability to interact with large amounts of customers (Verbeke and et. al, 2012). Eventually, this would help in ensuring that appropriate steps are taken to fulfil their needs and demands to the greatest extent possible. Even though some consider it as a challenge associated with using software and techniques of big data, but in the end it would aid SBT in gaining access to a large amount of data related to the customers and also ensure that these are used to improve operations of the company. Since traffic on networks provided by the company would increase substantially, management at SBT would have to apply for license that would allow them to operate at a very large network base and then provide appropriate solution to customers for accomplishing their needs and demands (Stallings, 2007).

On the other hand Nuechterlein and Weiser (2005), believes that there is another way in which the use of big data could affect network infrastructure of SBT, because of which overall operations of firm may be affected adversely. One of them is related to aspect of security. Since software of Big Data such as Hadoop, R, etc. are open source, any one can gain access to data sets acquired by the company, proving to be a very big danger for the organization and also its very existence in market (Bughin, Chui and Manyika, 2010). In this sense, it can be said that using the tools of big data could present its own set of unique challenges to company, to handle which major changes would have to be brought about in terms of network infrastructure used by the organization. Since there would be very less human interference in the process of collecting data about customers and storing them, stealing such information sets would become a lot simpler task to perform (Jeon, 2012). Thus it can be said that management of the company will have to hire not only different IT experts on the given field so as to ensure that such information sets are not lost; but they will also have to procure new and sophisticated servers so as to ensure data protection.

CONCLUSION

Big data is one of the major IT based tools being used by companies, regardless of the industry that they may be a part of, mainly because of reason that it provides them with the ability to develop highly effective business strategies. During the present study, it was observed that to use big data has its own set of unique challenges which then affect firms such as EE Limited or SBT, etc. in the telecommunications industry. This research revealed that to use the techniques of big data, management at EE Limited would have to procure new servers; while the management at SBT would have to change their network architecture so as to make it more conducive to firms' goals and objectives.

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REFERENCES

• Jeon, H. Y., 2012. Impact of Big Data: Networking Considerations and Case Study. International Journal of Computer Science and Network Security. 12(12).pp. 30-34.
• Townsend, A. M., 2013. Smart cities: big data, civic hackers, and the quest for a new utopia. WW Norton & Company.
• Nuechterlein, J. E. and Weiser, P. J., 2005. Digital crossroads: American telecommunications policy in the Internet age. Cambridge.
• Lu, J., 2008. Determinants of accepting wireless mobile data services in China. Information & Management. 45(1).pp. 52-64.
• Provost, F. and Fawcett, T., 2013. Data science and its relationship to big data and data-driven decision making. Big Data. 1(1).pp. 51-59.
• Stallings, W., 2007. Data and computer communications. Pearson/Prentice Hall.\
• Chen, Y., Alspaugh, S. and Katz, R., 2012. Interactive analytical processing in big data systems: A cross-industry study of mapreduce workloads. Proceedings of the VLDB Endowment. 5(12).pp. 1802-1813.

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