Abstract
In today’s culture, when everything is recorded digitally, from online surfing habits to medical records, individuals produce and consume petabytes of data every day. Every element of life will undergo a change thanks to big data. However, just processing and interpreting the data is insufficient; the human brain is more likely to find patterns when the data is shown visually. Data analytics and visualization are crucial decision-making tools in many different businesses. Additionally, it creates new opportunities for visualization, reflecting imaginative problem-solving with the aid of large amounts of data. It might be challenging to see such a large amount of data in real time or in a static manner. In this paper, the authors discuss the importance of big data visualization, the issues, and the use of several large data visualization techniques. The enormous data mine cannot become a gold mine until sophisticated and intelligent analytics algorithms are applied to it, and the findings of the analytical process are presented in an effective, efficient, and stunning way. Unsurprisingly, a plethora of Big Data visualization tools and approaches have emerged in the last few years, both as independent apps or plugins for data management systems and as a component of data management systems. The dataset obtained from Google Trends is prepared and experimented upon to visualize the Web search trends for Microsoft Power BI, Tableau, Qliikview, Infogram and Google Charts. Through this data visualization experiment various insights have been obtained that illustrates how sharply Power BI is gaining popularity as compared to rather modest trend of Tableau and other Data Visualization tools. Furthermore, the authors provide more insight on top listed countries searching for various Data Visualization tools and categorizing various Data Visualization tools of interest based of geographical locations. On account of these issues, this article provides an overview of the most popular and frequently used visualization tools and approaches for large data sets, concluding with a summary of the key functional and non-functional characteristics of the tools under consideration with a detailed comparative analysis of various Data Visualization tools web search trends.
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