Articles

Explain the use of Big Data in Blockchain Technology

by Alicia Adley Blockchain Council

As cryptocurrencies and other real-world uses of blockchain technology gain popularity, the amount of transactional data stored in multiple ledgers expands dramatically. The cost of storing these enormous data lakes on standard cloud storage providers such as AWS or Azure would be prohibitively high. The advent of blockchain technology has resulted in big global changes.


Using Big Data to Understand Cryptocurrencies


The usage of cryptocurrencies is spreading around the globe. Despite the fact that many people are still sceptical about bitcoin, one survey found that 19% of those asked had purchased some sort of cryptocurrency before 2019.


Both results are significant, showing that people are interested in it yet do not completely understand it. It's nothing to be embarrassed of if you don't understand crypto. Even market experts do not completely understand cryptocurrency, and the elements that determine its market value are still being debated.




Combining blockchain and Big Data: a new level of analytics


The incorporation of blockchain into the Big Data analytics process adds a new data layer. Most importantly, this data layer satisfies two fundamental Big Data analysis requirements:


Blockchain-generated Big Data is safe due to the network design.


Big Data on the blockchain is beneficial since information is well-structured, plentiful, and comprehensive, making it an excellent source for further study.


The data in the ledger may be used to energy trade, real estate, and a number of other sectors. As a consequence of this reality, various Big Data analytics improvements have occurred. For example, fraud protection is possible thanks to blockchain technology, which allows financial institutions to monitor every transaction in real time. As a consequence, rather than analysing prior fraud records, banks may detect potentially harmful or fraudulent transactions in real time and prevent the scam completely.




Obtaining Transactional Information


The most apparent benefit of applying big data methodologies to crypto blockchains is the ability to collect transactional data. This data will help identify how many individuals use a certain cryptocurrency, as well as how often and in what quantities the cryptocurrency is exchanged and received. This may help to influence activity selections as well as find new patterns in bitcoin use.




Data from Social Media


Data analysts may mine social data from social media sites and compare it to blockchain patterns such as the one outlined above. Because it is often considered that social media users and cryptocurrency users are in the same group, the two go hand in hand. Furthermore, real-world events in society and politics have been demonstrated to impact bitcoin market value. We will be able to uncover and investigate neglected themes by matching social data with blockchain data.




What Does All of This Mean for Investors?


Investing in cryptocurrencies may be a stressful experience due to the volatility involved and the difficulty in recognising market trends. Using big data to discover patterns in the blockchain might make investments more lucrative and less risky. This might persuade more investors to explore bitcoin as an investment alternative.




Finishing up


Blockchain and Big Data are, in fact, a perfect combination. The actual issue today is who will be the first to deliver the most suitable and best trained AI/machine learning model running on top of distributed, transparent, and immutable blockchain-generated data layers. This firm will bring in a lot of money and earn a lot of money.


This all demands blockchain education. The next generation must participate in blockchain degree and begin their adventure in the Blockchain world.








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About Alicia Adley Innovator   Blockchain Council

12 connections, 1 recommendations, 79 honor points.
Joined APSense since, September 3rd, 2019, From Brisbane, Australia.

Created on Nov 30th 2021 04:25. Viewed 177 times.

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