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HI6008 Business Research Assignment 1 Literature review Sample

HI6028 Taxation Law RIP Pty Ltd

HI6008 Business Research Assignment 1 Literature Review Sample Assignment

Topic: USES OF BIG DATA IN BUSINESS ORGANIZATIONS: A CASE STUDY OF TELSTRA

Table of Contents

Introduction. 2

Project objective. 2

Project scope. 2

Literature review.. 3

Research questions. 5

Design and methodology. 5

Limitations. 5

Research plan referred to the appendix. 6

Conclusion. 6

References. 7

Introduction

Big data are the goal setting processes of companies which are used to understand the working better inside the company to know their customers and to act according to their behaviors, necessities, and preferences (Hair, 2015). There are many such companies which are ready to expand their business with some goals which have the traditional data sets with the data collected through the media usage. There are again some of the browsers functioning as well as the analytics which is used in texts and even in censoring to get a clear picture of the customers to whom the ideas are shared (Zikmund et al. 2013). The usage of big data and the significance of using it can be important because it is used to describe the functioning that is high in the quantity that is high velocity, high volume, and high variety. These high usages will require new technologies and upgraded methods to store and analyze things which are used to develop the decisions and prove to discover and support to optimize processes. The analytics and insights of Telstra are building action plans to clear the objectives as an effort to succeed in order to engage the research with that of the customer engagement with the cross-functioning collaboration inside the company (Bryman, 2015).

Project objective

The objectives which are required to do a study on the whole research process of the company may be:

  1. To bring out the significance and the proper determination of the big data usage in Telstra.
  2. To make out whether the big data is presenting the analysis in a positive way or it is collecting the wrong information to lead the decision-making processes in a business.
  3. To focus on the cross functioning things if any and to maintain the loss and work on the improper information and correct the proper one’s accordance with the company profit.

Project scope

Big data is always used for big marketing and among which it has become the vital tool to work for companies to make out the big decisions which can be predictive in case of utilizing company’s data and processing of the operational challenges (Collis, 2013). The scope can include the software functioning in the company and the distribution of data and transferring programs through looping system with which a large amount of data may face challenges in storing, visualizing and querying the inadequate information to the whole system (Bakratsas et al.  2017). The scope of the project will further include the dealings and operation of the company’s terms with the uses of big data.

Literature review

The introduction to big data itself shows the transformation of small business into big by changing the data processes work with the big data management (John Walker, 2014). The big data has given birth to the big management which will look after the procedures and the working of the big data transferring it from the small data to handle the information system work and help in exhausting strategies to gain the market competition and the advantages which will not require to lose the information and manage the information to get stored when the company requires to keep a track record of it (Pääkkönen, 2015). The urgency in managing the small data from losing the databases and connecting to the primary sources will prove to handle the business organizations to change the management in analyzing the further data. The need for which the information is collected from the customer’s business concern can give birth to the analytics which may help in measuring the extracting information and further helps in generating and handling of the big data. Therefore to control the market strategies and in order to gain the profit, Telstra is taking the big data issue info notice to analyze the services and extra offers to make the operation more effective and working. The data are extracted from the outer sources to transmit information and the valuations from the system and put into the system by using the Extract Transform Load which helps the company to take down the informational data from outside and take back to load in the tools of the system to work in the operation and get it to the working process that can be further loaded on the database (Wu et al. 2014). The company will need to look at the rational and non-rational structures of the company designs which may get stored and separated according to the management processes.

There are certain critical requirements in case of the big data installation. They are:

  1. Scaling the secondary data management – most of the big data processes highly with the added drives which involve the workloads and needs to scale the data with many business track records. Big data applications may need to grow in the same way of simply adding the system processes which may incur growth to the primary system.
  2. Storage reduction – big data platforms are unique in the formation and they employ different types of compressed formats to data efficiently. This results in the optimization of the secondary storage of the application which is effective to be aware of.
  3. Supporting of storage target flexibility – companies like Telstra have multiple numbers of storage center’s which manages data to support the storage system that can support the attached commodity to the previously stored data. This should include the quick and easy storage to minimize the impact of data gain or loss.
  4. Network storage – the traditional involvement of finding the backup materials and efficient approaches would involve the backup data and reduce the recovery time objective that is materialized to restore the data and are meant to be recovered directly.

Big data releases the opportunities of changes which makes radical differences with the operations and making the decisions within the systems which make alternative sources to operate the making of technological support for analyzing the business dealings. The research gap may be analyzed with the indication of the loopholes that lead the project to look for the more of finding for the existing measures to add on to the research elements. There are some challenges and problems regarding the big data which lacks coordination within the database systems which provides the data and hosts to analyze the packages to perform various activities regarding the data mining with the process of structured query language. Big data may prove to cause the data to give out the wrong information at times which may certainly cause harm to the company’s data collection activity and that in any way be irrelevant to the operations of the company. The challenges may include the characterization of the various dimensions of management. This refers to the data acquisition and extraction of data integration and query processing. Big data do not arise out of a vacuum and the sources are generated with the reduction of information extraction process. The technical challenges can also affect to consider the automated resolutions. However, considerable additional work in data integration can provide some of the answers to be intact with the representation, aggregation and data integration. Methods of mining and querying data are differently traditional with the shapes that are dynamic, efficiently accessible and declarative mining interfaces.

 

Research questions

The primary questions of the big data may include the established truth or the actual things which the researchers are going to search. This can be mentioned as:

  1. Why is it necessary to study the big data process in a company like Telstra?

The secondary questions can be focused on the basis of some queries which may be studied supporting the secondary hypothesis. These may be:

  1. What does this big data represent and how it affects the different aspects?
  2. What is the requirement to research on the negative issues which may incur losses?

 

Design and methodology

The research design and methodology may be divided on the basis of qualitative research and quantitative research. They are as follows:

  1. The qualitative world of big data is still a necessary source of research which has a small part of the market research strategy within it. On the other hand, it is the stand alone role of generating the consumer and insight which has always fulfilled with the fundamental roles in delivering the qualitative questions behind the research trends and functioning.
  2. While in case of the quantitative analysis, the evaluation and security speak much of the measurement t requirements to which the variables need to the equator the market details and the big data processing would require maintaining those logical numerical values to keep track on the details of monetary easing, currency evaluation with interest rates.

Limitations

The limitations of the big data can be more of the challenging issues that comprise of the wrong questions, security questions, transferability. But the exact thing points on the management of tie which is the important thing in managing the survey processes as well as the correlations maintenance of the big data (Hashem et al. 2015). The technical endeavors will provide the analytical change which bothers the time limit of the research. Technical disorders may again cause to the lack of time management. This is the vital issue in conducting the research work which is to be done.

Lack of data may be another reason of limitation for the big data research. The limitation may require the lack of data collection while reviewing and surveying of the data. This may cause the analysis to be small in amount and the absence of bigger data cause to the lack of availability of sources. The time management with the proper data collection in the proper way is recommended to create a research and the limitations will make the usage policies work out positively in the next researches.

Research plan referred to the appendix

Conclusion

The whole of the research project shows the functioning of the technological aspects and the operations of the big data process which are used in the company working to deal with the inadequate software applications and storage of data collection which are in abundance to face the predictive analysis with proper method and planning. The proper management of the big data and all the information available will result in Telstra’s description to the operations of the big data process. This will provide a good knowledge on the company’s higher production process and a study of the customer’s behavior to the current issue regarding the company market strategies. The market may widen with the big data smoothing to all of the risks while business carries its effects to lead the problems in the future and try solving those for keeping the records and flourishing well.

References

Bakratsas, M., Basaras, P., Katsaros, D. and Tassiulas, L., 2017. Big Data Research.

Bryman, A. and Bell, E., 2015. Business research methods. Oxford University Press, USA.

Collis, J. and Hussey, R., 2013. Business research: A practical guide for undergraduate and postgraduate students. Palgrave Macmillan.

Colombo, P. and Ferrari, E., 2015. Privacy-aware access control for big data: A research roadmap. Big Data Research, 2(4), pp.145-154.

De Massis, A. and Kotlar, J., 2014. The case study method in family business research: Guidelines for qualitative scholarship. Journal of Family Business Strategy, 5(1), pp.15-29.

Hair, J.F., 2015. Essentials of business research methods. ME Sharpe.

Hashem, I.A.T., Yaqoob, I., Anuar, N.B., Mokhtar, S., Gani, A. and Khan, S.U., 2015. The rise of “big data” on cloud computing: Review and open research issues. Information Systems47, pp.98-115.

John Walker, S., 2014. Big data: A revolution that will transform how we live, work, and think.

Pääkkönen, P. and Pakkala, D., 2015. Reference architecture and classification of technologies, products and services for big data systems. Big Data Research, 2(4), pp.166-186.

Wu, X., Zhu, X., Wu, G.Q. and Ding, W., 2014. Data mining with big data. IEEE transactions on knowledge and data engineering, 26(1), pp.97-107.

Yu, S. and Liu, K., 2016. Special issue on big data from networking perspective. Big data research, 3, pp.1-1.

Zikmund, W.G., Babin, B.J., Carr, J.C. and Griffin, M., 2013. Business research methods. Cengage Learning.

Appendix

Figure: Representing the research planning process

(Source: As created by the researcher)

 

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