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Dr. Ganesh Kumar Dixit
Aryan Mandhana
Utkansha Vashistha
Nitesh Kumar Pandey
Keywords:
Data Analysis, Automation, Machine Learning, Artificial Intelligence, Big Data, Predictive Analytics, Data Processing, Business Intelligence, Workflow Automation, Data-Driven Decision Making.
Abstract:
In the technology of big records, the convergence of information evaluation and automation has revolutionized selection-making strategies across industries. This research paper explores the important function of facts analysis in extracting meaningful insights from sizable datasets and examines how automation complements analytical efficiency, accuracy, and scalability. By integrating device learning, synthetic intelligence (AI), and robot process automation (RPA), organizations can streamline workflows, lessen human intervention, and permit actual-time decision-making. The thesis offers intensive functions, equipment and frameworks used in automated data analysis, which highlights their applications in finance, health care, business intelligence and smart systems. Major challenges, including data quality, prejudice, security and moral concerns, are also discussed. In addition, new trends such as AI-driven analysis, cloud-based automation and future modeling are detected, providing insight into the future of automated data analysis. The purpose of this research is to contribute to an understanding of how automation is to shape the data analysis scenario, strengthen businesses and researchers with effective, scalable and intelligent decision support systems. Conclusions emphasize the transformation capacity of automation to unlock the entire value of date -driven insights.
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International Journal of Recent Research and Review
ISSN: 2277-8322
Vol. XVIII, Issue 1
March 2025
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PUBLISHED
March 2025
ISSUE
Vol. XVIII, Issue 1
SECTION
Articles
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