Exploratory Data Analysis (EDA) is a field of data analysis used to visually represent the knowledge embedded deep in the given data set. The technique is widely used to generate inferences from a given data set. Data set of current pandemic, the COVID-19 is widely made available by the standard dataset repository. EDA can be applied to these standard dataset to generate inferences. In this paper, data visualization technique is applied to the dataset and is used to formulate patterns for better insights on the effects of the pandemic with respect to the variables/ labels given in the dataset. A Web application tool called Jupyter Notebook is used to generate graphs using python language as it consists of libraries which are used for the process of EDA and the visualization is depicted for the attributes showing higher correlation. Based on the graphs obtained, we can draw conclusions from the current situation based on the data available, understand why a certain variable is increasing/decreasing with respect to another and what can be done to improve the drawbacks found.

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As technology is growing every day, the need for the technology is also becoming essential in every field. The amount of data generated by the healthcare industry is becoming tough to manage and to examine it in efficient manner for future use. In the healthcare field, massive amount of data is generated, from individual patient's information to health history, clinical data and genetic data. The analysis of patient's data is becoming more important, to evaluate the medical condition of patient and to prevent and take precautions for future. With the help of technology and computerized automation of machines, data can be analyzed in more efficient manner. Managing the huge volume of data has many problems interrelated to data security, data integrity and inconsistency. Process mining and data mining techniques have opened a new access for diagnosis of disease. Similarly, to provide effective treatment for a disease's triennial prevention, data mining can be used. Big data mining can aid in analyzing medical operation indicators of hospitals for a period to help hospital administrators provide data support for medical decision-making. In this manuscript, the various applications of big data mining techniques have been analyzed to improve the healthcare systems.

In this manuscript, we explore the network and cyber security challenges furthermore, issues of cyber or digital physical frameworks. (1) We epitomize the general work process of cyber or digital physical frameworks, (2) identify the conceivable vulnerabilities, assault issues, foes qualities and an arrangement of difficulties that are required to be addressed. A framework has been proposed for setting situation-apprehensive security structure for general digital or cyber physical frameworks with the implementation of biometrics.