How Blockchain Will Disrupt Data Science Part 1

Blockchain and Big Data are the leading new technologies that have already started changing the landscape of several industries, bringing radical changes in the way businesses are run. The best part is these two technologies are not mutually exclusive and forge unique implementation paths, totally independent of each other.

But where exactly these two technologies intercept? And what can be achieved if we apply these two technologies together?

To answer these questions, we first need to understand the Blockchain and Big Data separately.

Blockchain is a distributed ledger that records transactions in a tamper-free way. As we get to know the value of technology, many use cases are emerging. The demand for blockchain developers is higher than ever, which is one of the indicators that blockchain is getting more popular with each day that passes.

Data Science is dealing with extracting knowledge and insights from different data structures. This field includes data analysis, statistics, machine learning, and other methods utilized to understand the data. Information is often characterized as the new oil in the economic terminology, referring to its value. This is the reason why some of the most powerful corporations in the world deal mostly with data (Google, Facebook, Apple). Data Scientists are also in high demand, especially experts specialized in Big Data.

But unlike Fintech and similar industries where blockchain is starting to play a significant role, the exploration of big data is just beginning. For some, the connection between the two technologies is not clear and even non-existent.

The main shared thing between blockchain and data science lies precisely there — in data. The common theme lies in the following phrase — “data science for prediction; blockchain for data integrity.”

Impact of Blockchain on Data

The control of data is one area where blockchain can bring a positive impact on data science. According to a survey conducted among 16,000 data professionals, duplicate data was marked as one of the biggest challenges to data science. With the use of decentralized consensus and cryptography, this issue could be tackled, validating data and preventing any manipulations.

This is part one of our two-part series. If you want to discuss things further, feel free to join our Telegram group. We are always happy to chat with our supporters!