Advancing Cloud Data Analytics and Chatbots through Machine Learning Technology: Key Recommendations
Abstract
Cloud data analytics and chatbots represent pivotal facets of modern business operations, offering insights and automation capabilities. Machine Learning (ML) technology has been instrumental in enhancing their effectiveness. This paper presents recommendations to further harness ML's potential for these technologies. From deploying advanced ML algorithms for predictive analytics in cloud data analytics to optimizing chatbot interactions with natural language processing, these recommendations offer a roadmap for organizations to elevate their data-driven decision-making and customer engagement strategies.
References
Sheth, J. (2017). Chatbots as AI interfaces to business. Big Data, 5(1), 6-14.
Davenport, T. H., Harris, J., & Shapiro, J. (2018). Competing on talent analytics. Harvard Business Review, 96(10), 52-58.
Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2017). How ‘big data’ can make a big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 183, 319-330.
Kunduru, A. R. (2023). Security concerns and solutions for enterprise cloud computing applications. Asian Journal of Research in Computer Science, 15(4), 24–33. https://doi.org/10.9734/ajrcos/2023/v15i4327
Kunduru, A. R. (2023). Industry best practices on implementing oracle cloud ERP security. International Journal of Computer Trends and Technology, 71(6), 1-8. https://doi.org/10.14445/22312803/IJCTT-V71I6P101
Kunduru, A. R. (2023). Cloud Appian BPM (Business Process Management) Usage In health care Industry. IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, 12(6), 339-343. https://doi.org/10.17148/IJARCCE.2023.12658
Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Mobile Networks and Applications, 19(2), 171-209.
Manyika, J., Chui, M., Bughin, J., Dobbs, R., Bisson, P., & Marrs, A. (2016). Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly.
Kunduru, A. R. (2023). Effective usage of artificial intelligence in enterprise resource planning applications. International Journal of Computer Trends and Technology, 71(4), 73-80. https://doi.org/10.14445/22312803/IJCTT-V71I4P109
Kunduru, A. R. (2023). Recommendations to advance the cloud data analytics and chatbots by using machine learning technology. International Journal of Engineering and Scientific Research, 11(3), 8-20.
Kunduru, A. R., & Kandepu, R. (2023). Data archival methodology in enterprise resource planning applications (Oracle ERP, Peoplesoft). Journal of Advances in Mathematics and Computer Science, 38(9), 115–127. https://doi.org/10.9734/jamcs/2023/v38i91809
Kunduru, A. R. (2023). Artificial intelligence usage in cloud application performance improvement. Central Asian Journal of Mathematical Theory and Computer Sciences, 4(8), 42-47. https://cajmtcs.centralasianstudies.org/index.php/CAJMTCS/article/view/491
Kunduru, A. R. (2023). Artificial intelligence advantages in cloud Fintech application security. Central Asian Journal of Mathematical Theory and Computer Sciences, 4(8), 48-53. https://cajmtcs.centralasianstudies.org/index.php/CAJMTCS/article/view/492
WHIG, P. (2023). Blockchain Revolution: Innovations, Challenges, and Future Directions. International Journal of Machine Learning for Sustainable Development, 5(3), 16-25.
Whig, P., Kouser, S., Bhatia, A. B., Nadikattu, R. R., & Sharma, P. (2023). Explainable Machine Learning in Healthcare. In Explainable Machine Learning for Multimedia Based Healthcare Applications (pp. 77-98). Cham: Springer International Publishing.
Whig, P., Velu, A., Nadikattu, R. R., & Alkali, Y. J. (2023). Computational Science Role in Medical and Healthcare‐Related Approach. Handbook of Computational Sciences: A Multi and Interdisciplinary Approach, 245-272.
Kunduru, A. R. (2023). Cloud BPM Application (Appian) Robotic Process Automation Capabilities. Asian Journal of Research in Computer Science, 16(3), 267–280. https://doi.org/10.9734/ajrcos/2023/v16i3361
Kunduru, A. R. (2023). Machine Learning in Drug Discovery: A Comprehensive Analysis of Applications, Challenges, and Future Directions. International Journal on Orange Technologies, 5(8), 29-37.
Arjun Reddy Kunduru. (2023). From Data Entry to Intelligence: Artificial Intelligence’s Impact on Financial System Workflows. International Journal on Orange Technologies, 5(8), 38-45. Retrieved from https://journals.researchparks.org/index.php/IJOT/article/view/4727
Arjun Reddy Kunduru. (2023). The Inevitability of Cloud-Based Case Management for Regulated Enterprises. International Journal of Discoveries and Innovations in Applied Sciences, 3(8), 13–18. Retrieved from https://openaccessjournals.eu/index.php/ijdias/article/view/2247
Kunduru, A. R. (2023). DATA CONVERSION STRATEGIES FOR ERP IMPLEMENTATION PROJECTS. CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES, 4(9), 1-6. Retrieved from https://cajmtcs.centralasianstudies.org/index.php/CAJMTCS/article/view/509
Arjun Reddy Kunduru. (2023). Healthcare ERP Project Success: It’s all About Avoiding Missteps. Central Asian Journal of Theoretical and Applied Science, 4(8), 130-134. Retrieved from https://cajotas.centralasianstudies.org/index.php/CAJOTAS/article/view/1268
Kunduru, A. R. (2023). THE PERILS AND DEFENSES OF ENTERPRISE CLOUDCOMPUTING: A COMPREHENSIVE REVIEW. Central Asian Journal of Mathematical Theory and Computer Sciences, 4(9), 29-41.
Kunduru, A. R. (2023). Maximizing Business Value with Integrated IoT and Cloud ERP Systems. International Journal of Innovative Analyses and Emerging Technology, 3(9), 1-8.
Kunduru, A. R. (2023). Blockchain Technology for ERP Systems: A Review. American Journal of Engineering, Mechanics and Architecture, 1(7), 56-63.
WHIG, P. (2023). A Comprehensive Review of Mask Detection Using Artificial Intelligence: Methods, Challenges, and Applications. International Journal of Sustainable Development in Computing Science, 5(2), 11-20.
WHIG, P. (2023). A Comprehensive Review of Mask Detection Using Artificial Intelligence: Methods, Challenges, and Applications. International Journal of Sustainable Development in Computing Science, 5(2), 11-20.