Application of Big Data Analysis Method - MyAssignmenthelp.com

Question: Discuss about the Application of Big Data Analysis Method in Supply Chain. Answer: Introduction: Information and data have become the primary assets for any business organization. Massive clusters and huge number of data sets are used and applied by the business organizations. The data that is associated with these business organizations varies in terms of the information category along with the volume of the same. Big Data is a concept that includes the mechanisms and application of technology to efficiently handle and manage such different varieties and volumes of data in the business organizations. Use of information and data has amplified in the business organizations of the present times. The expansion of business organizations in the current times is massive and with the expansion of these business organizations, it has become necessary to manage the associated information as well. The requirements and the necessities to efficiently manage and retrieve the maximum information by the business organizations became a triggering event to go ahead with this particular research topic (Rodrguez-Mazahua et al., 2015). Also, Big Data has created a lot of stir in the world of technology and has emerged as a buzzword in the current times that also aided in the selection of the topic. A number of different new concepts and learnings were acquired by carrying out the research on the research topic. Big Data has been in existence since some time and is being applied in several different business sectors and organizations. The research allowed understanding of the Big Data technologies, tools and advantages that it provides to the business organizations. There are a number of Big Data technologies and tools that are used in the business organizations to handle and manage the information. Business Intelligence (BI) techniques are used in collaboration with Big Data to have better results and data operations to be carried out. Some of these technologies include data analysis, data mining, online analytical processing, data warehousing and a lot more (Najafabadi et al., 2015). There are several Big Data tools that are also available and most of these tools are open source in nature. Hadoop is one of the Big Data tools that aids in the execution of operations. Business organizations gain a lot of benefit and advantages from the use and application of Big Data. These advantages include better management and organization of the data and information that is associated with the organization (Wu Chin, 2014). Big Data analyzes the data by automatically carrying out data analysis on the information sets that reveals and brings out a number of different patterns and trends that are associated with these data sets. These results prove to be extremely beneficial for the organizations as they aid in understanding of the customers that are associated with the organization in terms of their likes, preferences etc. Also, a lot of market data can be analyzed using Big Data that allows understanding of the market performance and market trends (Provost Fawcett, 2013). Real-time information is also handled and monitored with the application of Big Data that is of prime importance in many of the business sectors such as public transport, finance, real estate, healthcare and many more. Big Data also allows easy storage of the data and information and there is also data retention processes carried out in which data sets that are no longer required are removed and discarded (Xin, 2016). Backups and disaster recovery tools that come along with Big Data help in the enhancement of security that is associated with the data sets. Interpretation The research aided in the enhancement of knowledge and also contributed a lot towards the learning in association with the use and application of Big Data in business organizations. Prior to the research conduction it was assumed that Big Data is concept that only includes the management along with the storage of organizational data. Little was known about the various operations such as analysis, mining, real-time view etc. that can be obtained using Big Data tools. Successful completion of the research allowed in the understanding of the potential applications that can be understood using this concept. Cost-effectiveness and cost-savings is desired by every individual and every business organization that is set up all across the globe. There is a lot of cost that is invested in the handling and management of information. These costs can be easily brought down by the use and application of Big Data in the organizations. The cost of set up and the infrastructure cost in association with Big Data are negligible. Also, cost of the tools is also not present as most of the Big Data tools are open source in nature. Therefore, the organizations gain and experience a lot of cost-savings in association with Big Data and its application (Stoica, 2016). Outcomes and Decisions The main aim and objective of the conduction of research was to understand the use and application of Big Data in the business organizations and industry sectors. The research unfolded various aspects that are associated with Big Data in terms of its technologies, tools along with the advantages and applications that can be executed in the business organizations. Big Data plays a significant role in the business organizations for information management, handling and storage. However, there are organizations that implement the Big Data tools and technologies without carrying out the necessary research and analysis on the needs and the requirements that are associated with the same. The need of Big Data in the business organizations depend upon a number of different factors such as the operations that are executed by the organizations, the entities that are associated with the organizations, sources of information, projects that are undertaken and many others. Therefore, the organizations shall first carry out an analysis of their needs before deciding to adapt Big Data tools and technologies (Perur, Kulkarni Kunchur, 2016). Also, it shall be made sure that the security of the data is maintained in the Big Data tools and technologies that are applied. There are options such as data recovery and data back-up that are present in the Big Data tools. However, it shall be ensured that the security mechanisms are maintained and are available as per the latest norms and technologies (Jhaveri, Gala Deulkar, 2015). Conclusion Big Data has allowed the business organizations to experience a number of benefits and advantages in terms of information handling, information management and cost-savings. There are various tools and technologies that come under Big Data and it collaborates with Business Intelligence (BI) techniques as well so that the data and information that is associated with the organizations is analyzed properly and accurately. Big Data analyzes the data by automatically carrying out data analysis on the information sets that reveals and brings out a number of different patterns and trends that are associated with these data sets. These results prove to be extremely beneficial for the organizations as they aid in understanding of the customers that are associated with the organization in terms of their likes, preferences etc. The need of Big Data in the business organizations depend upon a number of different factors such as the operations that are executed by the organizations, the entities t hat are associated with the organizations, sources of information, projects that are undertaken and many others. Planning and analysis is therefore very important so that the adequate benefits and advantages may be achieved. References Jhaveri, M., Gala, R., Deulkar, K. (2015). Big Data Feasible Solutions for Data Privacy Challenges. International Journal Of Computer Applications, 127(18), 1-4. https://dx.doi.org/10.5120/ijca2015906726 Najafabadi, M., Villanustre, F., Khoshgoftaar, T., Seliya, N., Wald, R., Muharemagic, E. (2015). Deep learning applications and challenges in big data analytics. Journal Of Big Data, 2(1). https://dx.doi.org/10.1186/s40537-014-0007-7 Perur, S., Kulkarni, G., Kunchur, P. (2016). Big Data Applications and Challenges: A Review. Bonfring International Journal Of Software Engineering And Soft Computing, 6(Special Issue), 117-120. https://dx.doi.org/10.9756/bijsesc.8256 Provost, F., Fawcett, T. (2013). Data Science and its Relationship to Big Data and Data-Driven Decision Making. Big Data, 1(1), 51-59. https://dx.doi.org/10.1089/big.2013.1508 Rodrguez-Mazahua, L., Rodrguez-Enrquez, C., Snchez-Cervantes, J., Cervantes, J., Garca-Alcaraz, J., Alor-Hernndez, G. (2015). A general perspective of Big Data: applications, tools, challenges and trends. The Journal Of Supercomputing, 72(8), 3073-3113. https://dx.doi.org/10.1007/s11227-015-1501-1 Stoica, I. (2016). Trends and challenges in big data processing. Proceedings Of The VLDB Endowment, 9(13), 1619-1619. https://dx.doi.org/10.14778/3007263.3007324 Wu, Z., Chin, O. (2014). From Big Data to Data Science: A Multi-disciplinary Perspective. Big Data Research, 1, 1. https://dx.doi.org/10.1016/j.bdr.2014.08.002 Xin, D. (2016). Application of Big Data Analysis Method in Supply Chain. Advances In Networks, 4(1), 1. https://dx.doi.org/10.11648/j.net.20160401.11