Abstract
Health care industry companies generate a large volume of raw data, often called big data, which reveals hidden patterns and knowledge for decision making. Data-driven decisions are more accurate than intuition because they use massive data. In exploratory data analysis, mistakes are detected, data is identified, assumptions are checked, and the correlation between the variables is determined. Analyzing data without inferences or statistical modeling is considered Exploratory Data Analysis in the context. Analysts forecast the future and reveal hidden patterns in any profession. In the recent past, data analytics can be seen as a technology that is accessible, and it is essential to healthcare, especially current findings in outbreaks and emergency circumstances. Exploratory data analysis is a crucial step when analyzing data, and the application of analytics in healthcare improves treatment by enabling preventive care. The elements that lead to heart disease are predicted in this paper. The research uses two sets of publicly accessible heart disease data. Two datasets contain 303 records with 13 attributes and 4238 with 16 attributes.
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