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Blockchain and big data

Blockchain and big data are both emerging technologies that are majorly used in the Agendas of organizations.

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Blockchain and big data

Blockchain has been in existence for two decades. It has existed for an extended period, but it came to the spotlight immediately after the news on Bitcoin spread worldwide.

Blockchain technology is termed as a type of technology that purely focuses on a well-distributed system (Yaeger et al., 2019). It helps in enhancing security to financial information as all the transactions are recorded in blocks.

The new transaction is permanently recorded in a new block, which should be made valid by the users linked to the network. Big data, on the other hand, can be defined as a compilation of massive datasets. Because big data is large and complicated, it may not be processed via ancient processing systems.

Firms can only use such datasets to approximate behavioral patterns and market trends (Yaeger et al., 2019). There is a need for big data analytics nowadays for the data to be processed effectively. Data analysis and prediction of marketing operations is the crucial role of big data analytics; this means that big data analytics plays a vital role in Blockchain technologies as a lot of financial information is recorded and stored in blocks.

Blockchain and big data are both emerging technologies that are majorly used in the Agendas of organizations. Both concepts are needed to change business operations radically and how the organizations are being managed in the future. In this paper, I will discuss various emerging concepts that explore big data and blockchain technology.

The first emerging concept is predictive analysis. This concept is used in the blockchain, and it makes use of big data (Chatterjee & Chatterjee, 2017). In the blockchain, data is transformed into currency, and the critical aspect here is data analytics. Blockchain also has several databases that store transactional data made up of individuals. In this case, the analysis should be carried out in blockchain. The ability to predict the future is the main goal for most organizations.

They were beginning from financial management to oncology and marketing. Stakeholders and customers should have a glimpse of what is expected in future and what should be done to enhance the success of operations. The kind of analysis carried out with the help of big data analytics is defined as predictive analysis (Ali et al. 2019).

The analysts, in this case, deal with massive datasets to extract essential and accurate information concerning customers’ preference for them to be offered customized products and services. With this kind of method, the data scientists will be able to utilize the data from various sources available in the network of blockchain. With the acquisition of data from multiple sources, the analysts can learn various trends from the predictions made, which will, in turn, help make informed and critical decisions (Sayadi, Rejeb & Choukar, 2018). It will also help reduce the resources used and save companies’ time using the traditional method.

The second emerging concept is integrity. The primary role set for blockchain is to improve the integrity of bitcoins. However, as bitcoins gain popularity, the underlying technology attracts more attention.

Blockchain technology has the capability of revolutionizing the way big data is looked. All the available information in the blockchain is trustworthy and secure. People with competent skills and knowledge go through the data to prove that the data is authentic and has never been duplicated from any other sources (Yaeger et al., 2019). As a result of technological advancement, some of the advanced applications companies can use to detect if the data is authentic and trustworthy have been developed.

Most companies are making use of blockchain to authenticate their data and enhance security as well. Most of the organizations, health organizations, retail and public

To mention a few, administrations have started using blockchain to handle their data to prevent the chances of data being hacked or leaked. For instance, in a healthcare organization, Firms cannot access data easily unless several signatures are provided. The integrity of information in any other organization apart from health care is verified automatically in the blockchain. The information should also be validated before any proceedings are carried out.

The third emerging concept is managing data sharing. Managing data sharing is among the ideas in the blockchain which make use of big data. The usefulness of blockchain technology in data management, especially in healthcare organizations, has raised a lot of concern in the industries and academics (Ali et al., 2019). Blockchain is known as distributed financial ledger, which provides append-only register and shared information of all the activities within the blockchain network and what happened to the participants.

The data sharing process management is a concept in the blockchain, which uses big data to achieve its set goals. After the given dataset has been analyzed, other analysts or data scientists may later carry out the data analysis process, which analysts had earlier analyzed, and the results acquired were wrong. Necessary precautions are required to prevent the use of erroneous information analysis. Blockchain is utilized to monetize the work by simply going through the analyzed data, which has been kept in blockchain platforms.

The fourth emerging concept in the blockchain, which uses big data, is preventing malicious activities. The algorithm applied in a blockchain does not allow any enterprise included in the blockchain network to pose threats to the whole system.

The blockchain (Yaeger et al. 2019). Suppose, by chance, the blockchain network nodes start behaving weirdly. In that case, data scientists can notice it quickly, and action is immediately taken to remove it, or the system can be made inactive. It is not easy for the computational powers of blockchain to be interfered with since the hacker will be forced to change one computational power; this will necessitate him to pool together various nodes of the blockchain network. Such counter-action may not be easy since the system is evenly distributed in nature.

The fifth emerging concept is real-time data analysis. This concept makes use of big data. Various transactions that are carried out in blockchain are secured online. It is, therefore, necessary for them to have a system that carries out real-time analysis. All the monetary transactions should be analyzed and completed in real-time (Chatterjee & Chatterjee, 2017). Such moves will necessitate any firm that needs to deliver real-time analysis to make use of blockchain technology to improve its operations and enhance customer satisfaction. The process is safe and does not need to get frustrated with errors as the transactions are being performed. They should also not get frustrated about the data which may be exposed to the public.

Conclusion

Blockchain technology is rapidly growing and based on its uses. It has a promising future for those using it and those who are planning to use it. The rate of growth in databases has made organizations prefer using emerging technologies. Data analytics play a crucial role in the blockchain. Data analysis and prediction of marketing operations are the critical roles played by big data analytics; this means that big data analytics plays a crucial role in Blockchain technologies as a lot of financial information is recorded and stored in blocks. This paper has discussed.

The emerging concepts which make use of blockchain technology and big data are enormous. Those concepts include; Prevention of malicious activities, Predictive analysis, managing data sharing, integrity, and real-time data analysis. Emerging concepts are essential since they help in improving the efficiency of blockchain technology. Most of the transactions require real-time analysis; Firms should carry out transactions in real-time monetary transactions. Data analysts and firms should prevent malicious activities as they cause adverse effects.

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