Abstract: With the expansion of information technologies and applications, a large amount of data is created, attracting both the academic community to use this information for knowledge extraction and the industry to build knowledge-based systems. Visualization tool, pattern mining from datasets, and assessing data drift for distinct attributes are three popular machine learning and data science applications. Visualization tool is a critical application in which the right depiction of data may assist in identifying the required features. Data visualization can take numerous graphical forms, such as bar charts and line charts, so that users with non-technical backgrounds can readily utilize the tools to extract information. Furthermore, in addition to visual representations of data, creating drift analysis of data in a certain time period is a standard procedure in several industries such as mHealth, e-commerce, and MOOC education. This paper presents a detailed review of various data visualization tools for different applications. At first, various data visualization tools for different applications are studied in detail. A comparative study is conducted with their merits and demerits for identifying the challenges in those tools and then this paper is concluded with suggestions of solutions for enhancing the efficiency of data visualization tools.

Keywords: Data visualization tools, information technology, visual representation, graphical form.

PDF | DOI: 10.17148/IARJSET.2023.10416

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