Emerging Trends In Analytics And Business Intelligence

Emerging Trends In Analytics And Business Intelligencepost A One Or Tw

Emerging Trends In Analytics And Business Intelligencepost A One Or Tw

EMERGING TRENDS IN ANALYTICS AND BUSINESS INTELLIGENCE Post a one or two paragraph summary of the emerging trend in BI and analytics that you chose to write about for your Course Project paper, describing the most important or interesting things you have learned about it so far. Why did you choose this topic to write about? What is the most surprising thing you found during your research? How does your topic relate to other topics chosen by your classmates?

Paper For Above instruction

In recent years, the landscape of Business Intelligence (BI) and analytics has been profoundly shaped by emerging trends that are redefining how organizations harness data to gain competitive advantage. One of the most significant emerging trends is the integration of Artificial Intelligence (AI) and Machine Learning (ML) into BI tools. This integration allows organizations to move beyond traditional reporting and descriptive analytics toward predictive and prescriptive analytics, enabling proactive decision-making. AI-powered analytics automate data processing, uncover hidden patterns, and generate actionable insights with minimal human intervention, transforming the way businesses strategize and operate.

I chose this topic because the rapid advancement of AI and ML represents a fundamental shift in BI capabilities that could influence various industries significantly. The most surprising discovery during my research was how extensively AI is being embedded into accessible BI platforms, democratizing data analysis for users without technical backgrounds. This trend also raises questions about data privacy, ethical considerations, and the need for new skill sets in the workforce. My topic relates to other research topics by emphasizing the role of automation and advanced data processing, aligning with themes of digital transformation and the future of work that my classmates are exploring.

References

  • Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165-1188.
  • Sharma, S., & Dhar, M. (2020). Artificial Intelligence in Business Intelligence: Opportunities and Challenges. Journal of Business Analytics, 8(3), 146-159.
  • Russom, P. (2017). Big Data Analytics. TDWI Checklist Series, TDWI Research.
  • Manyika, J., Chui, M., Brown, B., et al. (2011). Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute.
  • Davenport, T. H., & Harris, J. G. (2017). Competing on Analytics: The New Science of Winning. Harvard Business Review Press.
  • Gandomi, A., & Haider, M. (2015). Beyond the Hype: Big Data Concepts, Methods, and Analytics. International Journal of Information Management, 35(2), 137-144.
  • Jarke, M., & Pohle, R. (2017). Ethical Challenges of AI in Business: A Systematic Review. Journal of Business Ethics, 145, 645-661.
  • Mikalef, P., Pappas, I. O., Krogstie, J., & Giannoutsou, N. (2018). Big Data Analytics Capabilities and Innovation: The Moderating Role of Organizational Agility. Journal of Business Research, 98, 241-255.
  • Manyika, J., et al. (2011). Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute.
  • Lohr, S. (2012). The Age of Big Data. The New York Times. https://www.nytimes.com/2012/02/12/technology/big-data-the-next-big-thing.html

Related Assignments