Use Of Big Data Analytics In The Retail Sector †Free Samples

Question: Discuss about the Use Of Big Data Analytics In The Retail Sector. Answer: Background of the study At present days, data analytics has found its numerous applications in retail industry. It is extensively utilized for making strategic, operational as well as tactical procedures of decision-making. Gandomi and Haider (2015) stated that in the modern days, technology is driven across the world and customers in retail scenario are not accustomed to have digital comfort. However, they are savvy in using the process. Big data analytics can evaluate large amount of data in order to uncover the hidden patterns , correlations as well as other insights. Big data acts an important role in the process. Thus, it is required to understand what can make consumers tick and policies of the retail organizations. Being professional in software industry, the big data analytics is important that has a great impact on retail sector (Hu et al. 2014). The analytics can assist the organizations to identify the items that customers would likely to purchase together and what offers as well as promotions wo uld work best for the products as well as personalized offers. Thus, it is important to analyze the role that has a great impact on retail sector. Research questions What are the factors for establishment of retail sector at present days? What is the role of big data analytics in retail sector? What are the challenges might be faced by big data analytics in retail sector? What are the recommendations for minimizing the solution? Search terms Big data analytics: It is the procedure of examining large as well as varied data sets. Present trend of retail sector: The keyword helps to understand the present trends and factors responsible for the growth of retail sector References Gandomi, A., Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics.International Journal of Information Management,35(2), 137-144 Accessed from: https://www.sciencedirect.com/science/article/pii/S0268401214001066 Hu, H., Wen, Y., Chua, T. S., Li, X. (2014). Toward scalable systems for big data analytics: A technology tutorial.IEEE access,2, 652-687. Accessed from: https://ieeexplore.ieee.org/abstract/document/6842585/ Ghazal, A., Rabl, T., Hu, M., Raab, F., Poess, M., Crolotte, A., Jacobsen, H. A. (2013, June). BigBench: towards an industry standard benchmark for big data analytics. InProceedings of the 2013 ACM SIGMOD international conference on Management of data(pp. 1197-1208). ACM. Accessed from: https://dl.acm.org/citation.cfm?id=2463712 Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts.Big Data Society,1(1), 2053951714528481. Accessed from: https://journals.sagepub.com/doi/abs/10.1177/2053951714528481 Fan, J., Han, F., Liu, H. (2014). Challenges of big data analysis.National science review,1(2), 293-314. Accessed from: https://academic.oup.com/nsr/article-abstract/1/2/293/1397586 Groves, P., Kayyali, B., Knott, D., Kuiken, S. V. (2016). The'big data'revolution in healthcare: Accelerating value and innovation. Accessed from: https://repositorio.colciencias.gov.co:8081/jspui/handle/11146/465