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In big data, clustering is the process through which analysis is performed. Since the data is big, it is very difficult to perform clustering approach. Big data is mainly termed as petabytes and zeta bytes of data and high computation cost is needed for the implementation of clusters. In this chapter, the authors show how clustering can be performed on big data and what are the different types of clustering approach. The challenge during clustering approach is to find observations within the time limit. The chapter also covers the possible future path for more advanced clustering algorithms. The chapter will cover single machine clustering and multiple machines clustering, which also includes parallel clustering.

Pandemics are a severe threat to lives in the universe and our universe encounters several pandemics till now. COVID-19 is one of them, which is a viral infectious disease that increased morbidity and mortality worldwide. This has a negative impact on countries’ economies, as well as social and political concerns throughout the world. The growths of social media have witnessed much pandemic-related news and are shared by many groups of people. This social media news was also helpful to analyze the effects of the pandemic clearly. Twitter is one of the social media networks where people shared COVID-19 related news in a wider range. Meanwhile, several approaches have been proposed to analyze the COVID-19 related sentimental analysis. To enhance the accuracy of sentimental analysis, we have proposed a novel approach known as Sentimental Analysis of Twitter social media Data (SATD). Our proposed method is based on five different machine learning models such as Logistic Regression, Random Forest Classifier, Multinomial NB Classifier, Support Vector Machine, and Decision Tree Classifier. These five classifiers possess various advantages and hence the proposed approach effectively classifies the tweets from the Twint. Experimental analyses are made and these classifier models are used to calculate different values such as precision, recall, f1-score, and support. Moreover, the results are also represented as a confusion matrix, accuracy, precision, and receiver operating characteristic (ROC) graphs. From the experimental and discussion section, it is obtained that the accuracy of our proposed classifier model is high.

Blockchain is one of the growing technologies used for financial management systems. Financial data must be kept secure otherwise it can create a huge loss. So, whenever security features or technologies are developed must keep financial security as a priority. Stock market management is another area of finance sector that works on two concepts, that is, minimize the risk and maximize the profit. In this chapter, the authors discuss how blockchain technology is used for stock market analysis. Mainly blockchain will help us to make optimal stock exchanges through automation and decentralization. Stock market across the globe is rapidly using blockchain technology for the market transaction. Some of the country is still preparing themselves to use the blockchain technology. This technology offers huge potential for tracing securities lending, margin financing, and surveillance of system risk.

Blockchain is one of the fastest growing and most important technologies in the world. Most of the people think that blockchain is all about cryptocurrency or bitcoin, but it is beyond that. It is a technology that creates immutable and distributable data records that are shared between peers in network database systems and records digital events in such a way that it cannot be altered or recognized until it reaches the recipient. In recent times, many of the industries are using blockchain as a tool to innovate their functionality. Some of the well-known industries are banking sector, real estate, healthcare, internet of things, insurance, and many more. Out of these industries, healthcare is one of the industries that is adopting blockchain very rapidly. This chapter will discuss the blockchain and how it has transformed the healthcare industry.