Blockchain and Big Data Analytics - Technology Transformation and Beyond

Vijay Pravin Maharajan, Founder & CEO, bitsCrunch

“Change the world with technology”. This is evident when we look back at how each technological invention changed our lives. Blockchain and big data analytics are equally intelligent innovations that solve both data quantity and quality problems.

Simply put, blockchain technology is an append-only ledger that helps record transactions or information on a decentralized network. Big data analytics is the use of techniques to extract high-quality data from large-scale unstructured and semi-structured data sources.

The synergy of these two has enabled a diverse and unimaginable number of applications. It can be easily tied to cryptocurrency transactions from User X to User Y, NFT sales from User A to User B, and other transactions on digital assets or NFT marketplaces. These are real examples of the use of technology that combines blockchain and big data analytics.

So let’s get the big picture. According to research by Blockchain.com, there will be approximately 750 million blockchain transactions as of July 2022. Ethereum has about 360,000 of his NFT holders. These are vast amounts of user data that must be stored, protected and formatted for information. This is where blockchain and big data analytics go hand in hand.

How can blockchain help big data?

Combining blockchain and big data can solve a myriad of data-centric problems. Some of them are:

1. Data Accuracy and Completeness

Data collected from external sources often tend to be duplicates. Incorrect data can lead to lost revenue, cyberattacks, and compliance issues. Combining blockchain and data analytics can ensure the reliability of data records as large as terabytes and zettabytes.

The application is practiced by blockchain pioneers such as IBM, Coinbase, and Chain analysis to verify and secure documents and user data on the blockchain.

2. traceability

The transparency of distributed ledgers enables data traceability from source to destination. For example, in the order-to-track-to-delivery chain of activities on Amazon, data can be tracked for discrepancies related to orders. Giants such as Amazon, Walmart, Microsoft, Oracle and Huawei are already using blockchain for supply chain management.

3. data sharing

Data scientists and analysts use data from reports, analyses, and research. These data are stored on the blockchain, allowing more people to access them at the same time. Additionally, data scientists can monetize their derived and shared data analysis results on the blockchain.

The healthcare industry is choosing blockchain for this purpose, as fraud through falsification of patient medical records can have a negative impact on the reputation of each brand and the trust it has with its customers.

4. Real-time data analysis

Blockchain technology provides real-time data analysis with the highest accuracy. All cryptocurrency transactions include smart contracts. A smart contract holds the transferor, recipient, and time stamp data for a transaction. This helps us spot suspicious and fraudulent transactions. Banks can also implement blockchain technology for real-time data analysis and observe significant improvements in decision making.

5. Data prediction

Blockchain gets structured data from sources such as user accounts and devices. These data help data scientists predict outcomes relevant to customers and businesses. Market research, business investment, and industrial production can benefit from forecasted data. This data also helps us explore patterns and trends in each industry.

Blockchain technology has been adopted by 80% of the world’s listed companies who are customers and transaction data houses. At various stages of adoption such as research, pilot, development and production, companies are making their mark on this fast-growing technology. Paypal and Walt Disney started their blockchain penetration in 2014, but as of 2022, 27 global companies have fully functional products built on blockchain. For features such as real-time data analysis and traceability, blockchain has had a major impact when combined with big data analytics, and in the near future blockchain will survive if the infrastructure becomes more cost-effective.