LITERATURE REVIEW

 

 

 

 

 

Introduction

The modern environment is largely demarcated and run by the advanced methods of business and analytical frameworks. Newer systems of operations have been implemented by the different business companies within the different countries to host their business on a wider level. Big Data has been one of the most advanced and the prime forms of business analytics measurements that have revolutionised the art and the operations of the modern business context within the US. This report summarises six journal articles based on the aspects of the use of the Big Data in the business perspectives and their impacts on the business perspectives.

Article 1

Transformational Issues of Big data and Analytics in Networked Business

Jahshan, C., Vinogradov, S., Wynn, J. K., Hellemann, G., & Green, M. F. (2019). A randomized controlled trial comparing a “bottom-up” and “top-down” approach to cognitive training in schizophrenia. Journal of psychiatric research, 109, 118-125.

Aims

The aims of this research are to analyse the importance of the concept of big data on the performance of the business. In this case, an observation is made on the various issues related to the bid data are taken into consideration. The issues are the transformational one and the effort is to see how the business transactions are done in a useful way.

Reference and background research

The paper generally utilizes the generally accepted framework of the issues of the transformation of the big data on the analytics of business. It uses the existing methods for recognizable regulation of the business transactions involving the stakeholders, processes and products and the services. Big data generally used to meet the information of the both the external and the internal one of the company. They have used the technique of the machine learning for analysis.

Methods

The methods are in a broader way related to the approaches that are being taken for work. Approaches used for the business regulation using the bid data analysis are the top down approach (Jahshan, Vinogradov, Wynn, Hellemann & Green, 2019). This approach is used to show that the decision making is created by the management and is implemented in the policies of the company’s business. These decisions are taken by the executive decision maker.

Outcomes

The system of big data is increasingly matched with qualitative data which have a rate of measuring the calculation with less than 2% (Vaismoradi, Jones, Turunen & Snelgrove, 2016). The outcomes show that each and every big data has helped in the ejection of proper values that are required for the termination of the business goal. This is suggestive of a more detailed analysis.

Reflection

The research shows that the both the pre-existent extent and the newer implemented techniques can be successfully mated with the help of the bid data. The paper offers no complication in the eventual make out of the calculated measures and the procedures. The technique which has been used for big data is sentiment analysis which helps in giving out fruitful outcomes.

Article 2

Improvement of Firm Performance using big data Analytics

Albergaria, M., & Jabbour, C. J. C. (2019). The role of big data analytics capabilities (BDAC) in understanding the challenges of service information and operations management in the sharing economy: Evidence of peer effects in libraries. International Journal of Information Management, 102023.

Aims

            The aims of this research are to make a generic analysis of how the business firms have been improved with the help of big data. Business firms always un ups and downs in their goals so the importance of big data helps to make control of the crisis in a systematic and in a technical way.

Reference and background research

            The research paper is based on the existing application of the theories and the techniques which help in chalking out the apt calculate measure required for the business modules. The recent development of big data has enriched the work of the firm (Albergaria & Jabbour, 2019). The results also show the significant business analytics relationship.

Methods

            Methods are related to the approaches. The approach which has been taken by the company is to develop a mode of the bid data analytics capability or BDAC (Wamba et al. 2017). This is eligible for every firm. The BDAC model has drawn on the impact of the resource based theory (RBT) to have a fruitful analysis.

Outcomes

            The possible outcomes which are concluded from, this are, the organizations were not having proper productivity before, but the inauguration of big data analytics has augmented the production module of the business firms and it will increase in the future days. This has increased the profit outcomes of the business firms as well. The target of the company is to hold onto its goodwill and brand name in markets.

Reflection

            `This part significantly shows the use of combining both the automatics and the collaborative measures for initiation of the products. This has helped in the additional extra costs reduction of the company and saving its beneficial needs. The target is to have promotion and the projection of the needs of the product and it is gratefully meted with.

 

 

Article 3

Effect of Big data on Firm Performance: Econometric Analysis on Industry Characteristics

Liu, Y., Yin, Z., Zhang, Y., & Wang, Q. (2019, October). Mid and long-term hydrological classification forecasting model based on KDE-BDA and its application research. In IOP Conference Series: Earth and Environmental Science (Vol. 330, No. 3, p. 032010). IOP Publishing.

Aims

The aim of this part is to see the effects of the big data in the domains of the business firms. Additionally it also shows the effort of sketching the economic balance in the company, as the economy holds up the main backbone of a company. This is the most significant part of the research.

Reference and background research

            The new element of this part of the research is the use of the calculative measures and the algorithm designed to have an application on the classification of the budget balances and the imbalances. This is seen that the emergence of the big data has led to the measures of the stimulated investment that the business of the company has run into.

Methods

            The methods or the approaches which are used to have the balances and the measures of the econometric analysis are the use of the BDA assets (Liu, Yin, Zhang & Wang, 2019). The BDA has used the system of the panel data that is carrying essential information about the BDA solutions which is used for the increment of the company and targeted to meet the needs of the econometric gains to have a growth in productivity.

 

 

Outcomes

            The obvious outcome that is seen in the company is that, by using the BDA assets the econometric slices of the company have raised. The losses which the company was suffering were reduced in one taken step. This is the advantage of implementing big data in technological services of the company.

Reflection

            The company has shown how its services have improved to the implementation of the BDA assets which carries the function of raising new techniques and policies as and when met by the management. Smaller and the bigger firms are grateful for implementing such important devices in the work modules.

Article 4

Big data Analytics and its Potential Benefits in Health Organizations

Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N., & Lloyd, S. (2017). Quantum machine learning. Nature, 549(7671), 195-202.

Aims

            The aim of this research is to have an improvement in the healthcare organizations which can help them to cope up from instincts on the wastes of the resource and the performance problems that are present in their course of work which is to some extent a disadvantage of the company. The effort is to successfully have an improvement in the health departments in future days.

Reference and background research

            The research is mainly progressed to meet the disadvantages and the drawbacks which are highly faced by the health organization nowadays. The influences of big data can help in inauguration and initiating newer techniques which can otherwise be helpful for the organization. The health organization has readily accepted the use of the big data in their course of work.

Methods

            The approaches which have been forwarded by the big data is the use of the machine learning course in their work. The advantages of machine learning are wide enough. It helps in improving the personalization and the accuracy of the organization with the comprehensive measure of the profiles of the patients (Biamonte et al. 2017). The other methods are statistical analysis and the mining of data.

Outcomes

            The measures which have been put forward by the bid data are that the statistical technique which has been used for the accounting for an average percent of 48% which is good enough to have an improvement in the rules and regulation of the organization. Both of these are highly forwarded and the situation has an improvement of nearly 10% of its previous measures. The outcomes provide a suitable analysis of the productivity and the calculative powers and the measures.

Reflection

            The factors which can be recommended are that the health management should accept the policies of the strategies if the big data so that the eventual condition of the health organizations can be improved and the productivity of the organization can also have an augmentation in the national and the international business.

 

 

Article 5

Agile Manufacturing Practises: Role of big data and Business Analytics

Beck, K., Beedle, M., Van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., … & Kern, J. (2018). Manifesto for agile software development.

Aims

            The purpose of this study is to determine the role of the big data in the practices and the regulation of the agile. Effort is to discuss the advantages and the disadvantages related to the deployment of the concept of the big data within the operation of the company’s business modules.

Reference and background research

            The research will be showing the use of big data has created great impact in the agile practices. The effort is to break the concept of the agile in many units and hold in front of the mob to segment its purpose and benefits for the regulation of the operation.

Methods

            The methods which are used for the termination of the agile practices are the agile scrum methodology. This is basically a project which helps in development of the specific project (Beck et al. 2018). It has two or three springs, each sprint has the role of building the most vital feature and comes with the delivery of the product that is shippable.

Outcomes

            The resultant outcome of it is that the related product which has come out from this methodology is swift enough and has a right grip on the advanced approaches and the narrower techniques of the growth of the business firms. The measures of this are the calculative and the immediate calculation of the specified research and techniques.

Reflection

            The reflections of this is that the advantages and the disadvantages of the business firms are evaded from its module with the right kind of agile practices which are required to have a progression of the company. Agile practices are significant for the success and development of the company which is related to the growth and development of the spare parts of the company.

Article 6

Strategic value of Big Data and Business Analytics

Fragkiadaki, K., Arbelaez, P., Felsen, P., & Malik, J. (2016). Learning to segment moving objects in videos. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4083-4090).

Aims

            The aim of this research is to have a detailed analysis of the strategic issues of the company. The stratagems are highly a necessity of the company to augment its profit, benefits and the investments which are required for the customers and the management.

Reference and background research

            The rapid accumulation of the data in diverse units and variety of numerous sources has been an intrigue of the big data in the business analytics. The businesses are exploring the system of uncoiling knowledge of the hidden truth which can help in decision making and logical purposes.

Methods

            The methods which are used to develop the procedures are the sedition of the segment learning and implementing its benefits in the smaller and the larger business firms (Fragkiadaki, Arbelaez, Felsen & Malik, 2016).

Outcomes

            The resultant outcome of this is that the measures and the drawbacks of the business firms are meted out which are lining from the segment of learning is incorporated in the business

Reflection

            The research has successfully checked out the segment learning to have an improvement in the strategic issues for the company and make sure that these improvements contribute to the development of the business firms in future.

 

 

References List

Albergaria, M., & Jabbour, C. J. C. (2019). The role of big data analytics capabilities (BDAC) in understanding the challenges of service information and operations management in the sharing economy: Evidence of peer effects in libraries. International Journal of Information Management, 102023.

Beck, K., Beedle, M., Van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., … & Kern, J. (2018). Manifesto for agile software development.

Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N., & Lloyd, S. (2017). Quantum machine learning. Nature, 549(7671), 195-202.

Fragkiadaki, K., Arbelaez, P., Felsen, P., & Malik, J. (2016). Learning to segment moving objects in videos. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4083-4090).

Jahshan, C., Vinogradov, S., Wynn, J. K., Hellemann, G., & Green, M. F. (2019). A randomized controlled trial comparing a “bottom-up” and “top-down” approach to cognitive training in schizophrenia. Journal of psychiatric research, 109, 118-125.

Liu, Y., Yin, Z., Zhang, Y., & Wang, Q. (2019, October). Mid and long-term hydrological classification forecasting model based on KDE-BDA and its application research. In IOP Conference Series: Earth and Environmental Science (Vol. 330, No. 3, p. 032010). IOP Publishing.

Vaismoradi, M., Jones, J., Turunen, H., & Snelgrove, S. (2016). Theme development in qualitative content analysis and thematic analysis.

Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356-365.

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