Blockchain is emerging as a very important technology today due to the growth of cryptocurrencies such as Bitcoin and the influence of decentralized finance.
According to Allied Market Research, the global cryptocurrency market was valued at $1.49 billion in 2020, reaching $4.94 billion in 2030. The CAGR(Compound Annual Growth Rate) from 2021 to 2030 is expected to grow by 12.8%.
Many companies are investing heavily in data science as a priority. In a recent Gartner survey of more than 3,000 CIOs, respondents cited analytics and business intelligence as the most differentiated technologies in their organizations. CIOs in the survey see these technologies as the most strategic for their companies and invest accordingly.
Blockchain and data science have clear growth prospects and are technology fields with great potential for future development with differentiated technologies. So it’s a very interesting topic to think about the correlation between these two technologies. Before looking at this topic, you will need to look at each technology for a moment.
What is Blockchain?
Blockchain, as a database, stores data in an electronic format. Blockchain is best recognized for its use in cryptocurrency systems such as Bitcoin to guarantee secure and decentralized transaction records.
The revolutionary feature of blockchain is that it guarantees data integrity and security. At the same time, it develops trust without the need for a third party.
What is Data Science?
Data science is a discipline that blends the domain knowledge with programming skills, as well as a grasp of mathematics and statistics, to extract valuable insights from data.
Data scientists use machine learning algorithms to calculate numbers, text, images, videos, and sound in order to build artificial intelligence (AI) systems that carry out functions that would otherwise require human intellect.
These tools generate insights that allow analysts and business users to apply their knowledge directly to real-world business results.
What is different between Blockchain and Data Science?
The main distinction between blockchain and data science is that blockchain records and validates data, allowing for payments in real-time.
Meanwhile, data science is often used to evaluate executable intellect on existing data and improve data analysis.
The aim of the blockchain is to guarantee data integrity. Data science, on the other hand, is intended to predict data.
What is the relationship between Blockchain and Data Science?
What these two technologies have in common is data at the core. When blockchain is about recording and verifying data, data science provides insight for problem-solving and decision-making.
Both technologies apply algorithms to interact with other data segments.
From the perspective of data science, blockchain provides innovative technologies for verifying and recording data. Blockchain, which excels in verifying data, differs from data science for data prediction, but it is a field that deals with data as an entity, and data science and blockchain have a very close relationship.
Most companies have a huge amount of data. Most of these data are scattered, so it takes a lot of time to organize them. In addition, various human errors affect the accurate analysis. In addition, the risk of data damage is scattered when data is concentrated and stored in one place.
However, blockchain technology is a method that incorporates new technologies into data processing methods. It enables a distributed structure that allows data analysis directly from individual devices without having to collect data together.
Data that is generated through blockchain can help boost data science. The data is validated and structured so that it is more reliable. This helps to improve the accuracy of data when it is combined and analyzed by corporations.
In other words, blockchain technology has several advantages that make it a good choice for data science applications.
Advantages of Data Science
Data Quality
The first advantage of blockchain technology is that the data quality is excellent. This is because the decentralization of the blockchain is verified and approved, making the data immutable. In other words, it becomes impossible to modify the data for any purpose.
In addition, blockchain technology is that the data is well structured and the schema to document. This makes it easier for data science work to be done in a more predictable way.
Data Tracking
Data tracking is possible. The blockchain stores where the transaction came from, when it happened, how many assets were involved, and how much money was used. Plus, most public blockchains have a search function so you can investigate information on the blockchain.
Real-time data monitoring is a good way to prevent and confirm crime. However, data scientists have thought that this type of analysis is impossible. Today, however, thanks to the distributed nature of blockchain, companies can detect any anomalies in their databases from scratch.
Data Sharing
Users should not provide their personal information when using blockchain technology. Blockchain does not require users to provide personal information, which is very important in a world where it has become extremely difficult to maintain personal privacy.
This helps data scientists avoid the challenge of European security regulations, which require personal data to be anonymous before processing.
Collecting data from the blockchain can be a tricky process. However, data scientists can still do this effectively through the use of already prepared datasets, the use of blockchain-specific ETL or APL tools, or other types of commercial solutions.
Conclusion
Data science is constantly evolving. It changes quickly, and now it is changing even more with the help of blockchain technology. This new technology makes it possible to keep track of everything that happens and to keep your data safe. That means data scientists can do things that were once impossible.
Blockchain technology is a relatively new technology that has been shown to be effective in data science. Companies who have experimented with it agree that it works well.
If blockchain technology continues to develop and more innovations happen, then it will have a big and important impact on data science. This is because blockchain technology can be used for many different and specific purposes that will help improve data science.
Summary
The technology industry is rapidly evolving and changing, and many organizations are conducting research in the fields of blockchain and data science. There is a lot of potential for growth in both technologies, as well as distinct of them. As a result, it’s a fascinating issue to consider the relationship between these two technologies.
Author Bio
Joshua Choi is the founder of learningsmartly.com, a website that provides people with information and resources on how to learn new skills such as technology, business, language, and personal development. He is passionate about learning new things and enjoys reading and playing golf.
