Blockchain has been causing ripples across major industries and verticals in the recent couple of years. We are seeing the future potential of blockchain technology that is scaling beyond just cryptocurrencies and trading.
It is only natural that Blockchain is going to have a huge impact on Data Analytics, another field that has been booming and seems to continue in the same trajectory for the foreseeable future.
However, very little research has been done on the implications of blockchain on Data Science or the potential of Data Science in Blockchain.
While Blockchain is about validating data and data science is about predictions and patterns, they are linked together by the fact that they both use algorithms to control interactions between various data points.
Blockchain in Big Data Analytics
Big Data has traditionally been a very centralized method where we had to collate data from various sources and bring it together in one place. Blockchain, considering its decentralized nature can potentially allow analysis of data to happen at the origin nodes of individual sources.
Also, considering that all data parsed through blockchain is validated across networks in a fool proof manner, the data integrity is ensured. This can be a game changer for analytics.
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With the digital age creating so many new data points and making data more accessible than ever, the need for diving into depth with advanced analytics has been realized by businesses around the world. However, the data is still not organized and it takes a very long time to bring them together to make sense of it.
The other key challenge in Big Data remains data security. Centralized systems historically have been known for their vulnerability for leaks and hacks.
A decentralized infrastructure can address both of the above challenges enabling data scientists to build a robust infrastructure to build a predictive data model and also giving rise to new possibilities for more real time analysis.
Can Blockchain Enhance Data Science?
Blockchain can address some of the key aspects of Data Science and Analytics.
Data Security & Encoding:
The smart contracts ensure that no transaction can be reversed or hidden. The complex mathematical algorithms that form the base of Blockchain are built to encrypt every single transaction on the ledger.
Origin Tracing & Integrity:
Blockchain technology is known for enabling P2P relationships. With blockchain technology, the ledgers can be transparent channels where the data flowing through it is validated and every stakeholder involved in the process is made accountable and accessible. This also enables the data to be of higher quality than what was possible with traditional methods.
Data science itself is fairly new and advancing in recent years. Blockchain Technology, as advanced as it seems, is still at what is believed to be a very nascent stage. We have been seeing an increasing interest in data being moved to the cloud and it is only a matter of time when businesses will want it to be moved to decentralized networks.
On the other hand, blockchain’s network and server requirements are still not addressed and data analytics can be very heavy on the network, considering the volume of data collected for analysis. With very small volumes of data stored in blocks, we need viable solutions to make sure data analysis in blockchain is possible at scale.
At Pyramidion, we have been working with clients globally on some exciting blockchain projects. These projects are being led by visionaries, who are looking to change how the world functions, for good. Being at the forefront of innovation, where we see the best minds working on new technologies, ICOs and protocols, we strongly believe it is only a matter of time before the challenges are addressed and Blockchain starts being a great asset to another rapidly growing field like Data Science and Data Analytics.