Introduction to Blockchain and What it Means to Big Data

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An Introduction to Blockchain Technology

Blockchain development technology has been around for almost two decades. But it came into the spotlight only after the news of Bitcoin spread across the globe. The Blockchain is a revolutionary technology that works on a ‘distributed ledger system’. It is a decentralized network topology with a heightened level of security. All the transactions are stored in individual blocks. Each new transaction is recorded in a new block which must be validated by the users connected to the network. All these blocks are interlinked in the form of a chain. Hence the name ‘Blockchain’. The timestamp of each transaction is recorded in a tamper-proof manner. In other words, any addition or changes in data is recorded with a time stamp that cannot be altered. Because of the high level of transparency in the system, the Blockchain is much more secure and the data integrity is preserved.

The Blockchain development technology also has a feature called smart contracts. The smart contracts functionality is highly useful for automatically settling the transactions in a network. Developers can code in the specifics about the payments like wallet address, bank account information and beneficiary details. When the transactions are executed, it can be validated by the users connected to the network and settled automatically.

Blockchain and Big Data

Big Data, as the name suggests, is the compilation of massive datasets. Since the data is extremely large and complex, it cannot be processed through the traditional data processing systems. These data sets can be used for estimating behavioral patterns and market trends. The demand for Big Data Analytics is very high nowadays. The primary factor that drives the demand so high is the ever-increasing real-world applications of Big Data. Lots of transactional data are stored in different forms of ledgers on the internet. Many enterprises use a Cloud-based web storage to record and store all this information. This can be a costly affair for companies and institutions. Analyzing this data to predict market response is one of the major roles in Big Data Analytics. This is where Blockchain comes to the aid of Big Data.

Blockchain can be an efficient mode for online data storage. In addition to this, the decentralized network can grant access to many users. Various parties in a transaction store the transactional information in different ledgers. All these parties can be granted access to one single network with the help of Blockchain. Transactions can be recorded in the network which can be further validated by all the concerned parties. Since all the information will be stored in the Blockchain it will be convenient to access these details. Because of the design of the Blockchain technology, users can view historical transactions effortlessly. Tracking the origins of a transaction becomes effortless.

Using the Blockchain development technology for storing Big Data can be cost saving for companies. Blockchain has the capacity for storing vast amounts of data, and that took over long periods of time. Companies can opt for storing the data on a decentralized network structure with the use of Blockchain. Owing to this technology, enterprises will not have to incur costs for data storage platforms. An additional benefit of using the Blockchain to handle Big Data is the application of Smart Contracts functionality. By coding the necessary information, the smart contracts can perform transactions automatically. This can have a major impact on reducing the transaction costs.

Real Life Scenario of Blockchain and Big Data

One of the real-world instances where Blockchain and Big Data were used hand in hand was in the banking sector in Japan. Approximately 50 Banks formed a consortium and arranged with Ripple. Ripple is an open sourced network built on the Blockchain technology. Globally, Ripple ranks the third in market capitalization. This alliance was entered with the intent to use the Blockchain technology for risk-free and low-cost transactions. This was made possible by revamping the traditional banking model. The orthodox model has many parties involved and has much more risk factors, in order to plug in the risk and implement control points, the banks must incur additional costs. These costs can be saved with the use of Blockchain networks. The collaboration of these banks also reduced the transaction time significantly.

Conclusion

Big Data Analytics can have an additional layer of security, if implemented on a Blockchain network. The first layer of security can be attributed to the network architecture of the Blockchain. Unlike the traditional methods, the information in the network is secure and cannot be duplicated. Secondly, using Blockchain to store Big Data can make the information structured and valuable. Performing analysis on data becomes much more efficient and easier. Using the Blockchain application development technology can also help fraud detection. Banks and financial institutions can trace a transaction to its origins and detect any anomalies.

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