International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Enhancing Data Analysis through Machine Learning: Algorithms, Applications, and Challenges in the Era of Big Data |
|---|---|
| ABSTRACT | In the contemporary era of big data, traditional data analysis techniques often struggle to process large-scale, high-dimensional, and unstructured datasets effectively. Machine learning (ML), as a core domain of artificial intelligence, provides advanced computational approaches that enable automated pattern recognition, predictive modeling, and data-driven decision-making. This paper presents a comprehensive study of the role of machine learning in modern data analysis, focusing on key algorithms such as linear regression, decision trees, support vector machines, and neural networks. It explores how these algorithms contribute to extracting meaningful insights across various domains, including finance, healthcare, and e-commerce. Furthermore, the paper critically examines the practical challenges associated with machine learning implementation, including data quality issues, algorithm selection complexity, lack of model interpretability, and high computational requirements. Potential solutions such as data preprocessing techniques, model optimization strategies, and privacy-preserving mechanisms are also discussed. The study highlights that while machine learning significantly improves the accuracy and efficiency of data analysis, its successful adoption requires a balanced integration of technological advancement, transparency, and ethical considerations. This research aims to provide a structured understanding of machine learning applications in data analysis and serve as a reference for future research and real-world implementation. |
| AUTHOR | MANSI SINGH THAKUR, SUNNY W THAKARE Department of Computer Science and Engineering, Parul Institute of Technology, Parul University, Vadodara, Gujarat, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404025 |
| pdf/25_Enhancing Data Analysis through Machine Learning Algorithms, Applications, and Challenges in the Era of Big Data.pdf | |
| KEYWORDS | |
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