If Big Data is the quantity, blockchain is the quality
Blockchain is open-source code.
Today, network behavior and economies are facing the risk of turning into monopolies as the need for trust and security as intermediaries such as banks or social media giants turn into gatekeepers who possess the power to curtail innovation and centralize their dominance. A new system has emerged which harnesses the potential to disrupt the analytics field, whilst bringing various other benefits to the practice of data analytics.
So how do two technologies collide? First, Blockchain is an electronic, distributed ledger which ensures security and integrity of transactions, stored on a network of computers.
Hence, it will facilitate small businesses or individual data scientists with a cloud computational power equivalent to that of a supercomputer. Moreover, the language which most data analytics models read consists of convoluted queries for machines to be able to process.; thereby, utilizing these technologies for predictive analytics would be more accessible and economical to the mass.
Due to blockchain’s secured design as a decentralized ledger, information integrity is preserved network-wide each time a ‘block’ verifies the entire transaction history, making it impossible to manipulate and mutate data. Although the information stored in blockchain is encrypted, it acts as a source of data that brings various applications to Big data. Specifically, it allows events to be recorded and validated in real-time, enabling a high degree of data transparency in analytics as well as establishing trust, since the linked chains ascertain the origin and activities.