This week’s article provided a case study approach which highlights how businesses have integrated Big Data Analytics with their Business Intelligence to gain dominance within their respective industry. Search the UC Library and/or Google Scholar for a “Fortune 1000” company that has been successful in this integration. Discuss the company, its approach to big data analytics with business intelligence, what they are doing right, what they are doing wrong, and how they can improve to be more successful in the implementation and maintenance of big data analytics with business intelligenceYour paper should meet the following requirements:
- Be approximately four to six pages in length, not including the required cover page and reference page.
- Follow APA 7 guidelines. Your paper should include an introduction, a body with fully developed content, and a conclusion.
- Support your answers with the readings from the course and at least two scholarly journal articles to support your positions, claims, and observations, in addition to your textbook. The UC Library is a great place to find resources.
- Be clearly and well-written, concise, and logical, using excellent grammar and style techniques. You are being graded in part on the quality of your writing
Elhoseny, M., Kabir Hassan, M., & Kumar Singh, A. (2020). Special issue on cognitive big data analytics for business intelligence applications: Towards performance improvement. International Journal of Information Management, 50, 413–415. https://doi.org/10.1016/j.ijinfomgt.2019.08.004
Integrated Understanding of Big Data, Big Data Analysis, and Business Intelligence: A Case Study of Logistics. Sustainability 2018, 10(10), 3778; https://doi.org/10.3390/su10103778 There is a PDF link above the Abstract.
Krivo, A., & Mirvoda, S. (2020). The Experience of Cyberthreats Analysis Using Business Intelligence System. 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT), Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT, 2020 Ural Symposium On, 0619–0622. https://doi.org/10.1109/USBEREIT48449.2020.9117694