Utilizing Machine Learning in Big Data Visualization: A Systematic Review - Ade Kurniawan; Aldi Rosyid; Ade Rudi Masa’id; Wendi Usino (Universitas Bandar Lampung (UBL), 2026)
This systematic review examines the existing literature on data visualization approaches for big data, aiming to identify key challenges, emerging trends, and promising solutions. The review highlights the growing importance of data visualization in extracting meaningful insights from large and complex datasets. It underscores the unique challenges posed by the scale and multidimensionality of big data, emphasizing the need for innovative visualization techniques. The paper explores various data visualization methods currently employed in big data analysis, discussing their strengths, limitations, and potential areas for future development. The review concludes by emphasizing the importance of continued research in this field to improve the accessibility and effectiveness of big data visualization for a wide range of applications.