Blockchain and big data are changing the way organizations function. The majority of us think these technologies are incompatible and must be used separately, each following its own set of rules. That, however, is not the case.
The decentralized ledger of the blockchain ensures data security while data science concentrates on utilizing data for effective administration. Blockchain technology is now trending due to recent developments in decentralized finance, the meteoric rise of Bitcoin and other cryptocurrencies, and the never-ending NFT craze.
If you’re a data scientist interested in applying statistics and Machine Learning to tackle some interesting problems, you could find Blockchains to be an appealing source of high-quality data to work with.
This blog, however, makes an effort to address these concerns by presenting an objective analysis of the status quo and emerging developments at the intersection of Data science and Blockchain technology.
What Exactly Is a Blockchain?
As a distributed online ledger, a blockchain keeps track of all financial dealings. Since there is no centralized authority over this ledger, it is immune to manipulation.
Due to the fact that modifying any given block would inevitably affect subsequent blocks, the information stored in a blockchain cannot be modified after it has been written. Once a restriction on a prior block is lifted, it applies to all subsequent blocks as well. Because of this, it’s possible that not even a modification in a single block would go unnoticed.
Over the past few years, both the demand for Blockchain engineers and the number of projects working on new blockchain applications have skyrocketed.
Freelancer websites like UpWork have noted that blockchain specialists are still in demand. Experts in other subjects, such as legal studies, are also considered to benefit greatly from familiarity with blockchain technology.
What is Data Science?
Data science is one of the most exciting areas of IT right now. Plenty of progress is made in the field’s specialized areas, such as Predictive Analytics, Diagnostic Analytics, and Descriptive Analytics.
The purpose of data science is to glean useful information and insights from datasets, both structured and unstructured. The field of data science encompasses cutting-edge methods like machine learning, data analysis, statistics, and others that are used to gain insight into natural processes by analyzing large amounts of data.
Blockchain and Its Connection to Data Science
Parts of Data science have not been substantially researched utilizing Blockchain, in contrast to industries like Fintech, healthcare, and supply chain where Blockchain is now widely employed. Those who hold this view argue that there is minimal causality between the concepts.
To begin, data is fundamental to both blockchain and data science. Data science analyzes the data stored and verified by blockchain to draw conclusions that can be put to use. They both make use of algorithms designed to regulate the interplay of various parts of data. A common refrain will emerge, to wit: “Data science for prediction; blockchain for data integrity.”
Benefits of Blockchain to Data Science
Here are a few examples of how Blockchain might improve Data Science:
1. It Enables Real-Time Analysis
It’s not easy to analyze data in real time. For the best results in recognizing fraudsters, it is best to keep tabs on any and all changes in real time. However, for a very long time, real-time analysis was not practical. With Blockchain’s decentralized ledger, companies can spot database inconsistencies almost instantly.
Excel spreadsheets have the unique capability of displaying live updates to data. Blockchain is similar in that it allows several users to operate in unison on the same data at the same time.
2. Allows for Tracking of Information
Blockchain makes it possible for users to communicate directly with one another. If, for example, a published account inadequately explains any approach, a colleague can study the entire procedure and identify how the results were acquired.
Through the ledger’s open channels, anyone can determine if data is trustworthy, how to store and update it, where it came from, and how it should be used. In conclusion, users will be able to track data from the moment it enters a blockchain to the moment it leaves a blockchain.
3. It maintains a high standard for data quality
The information recorded in the blockchain’s digital ledger is distributed among multiple nodes, both public and private. At the entrance point, the data is reviewed and examined before being added to the rest of the blocks. This method can be used to verify the accuracy of the information.
4. Improved Data Integrity
In the last decade, companies have focused mostly on increasing their ability to store data. That matter was resolved by the close of 2017. The integrity of the data is currently a top priority for most firms.
That is due, in large part, to the fact that businesses nowadays collect information from a wide variety of locations. There is a chance that any data, including that compiled in-house or obtained from government sources, is inaccurate. It is also possible that other data sources, such as social media, will out to be unreliable.
5. Facilitates Information Exchange
Businesses gain a lot from efficient data transfers. The task is quite difficult when dealing with paper files. When the contents are needed elsewhere, the challenge becomes much more challenging. These papers could make it to the other division, but it could take some time, and there’s always the chance that they’ll get lost in transit.
Most data scientists are currently intrigued by Blockchain since it permits multiple users to view the same data in real time. Therefore, when information is openly shared, administrative tasks are completed more quickly.
6. It Helps to Establish Credibility
You need to be aware of the fact that prejudices tend to surface when there is only one person in charge. It’s risky to put all your eggs in one basket. Many companies have strict policies against allowing others to access their information due to trust issues.
Technology advancements like Blockchain have made it so that mistrust in other parties is no longer an obstacle to communication. There is a complete breakdown in communication as a result of this. Companies can work together effectively when they share the information they already have.
Conclusion
Data science is an ever-evolving field. Integrating Blockchain technology will allow for transparent record keeping and excellent security, allowing data scientists to achieve various goals that were previously thought to be impossible.
Even though Blockchain is still in its infancy as a technology, early results from several businesses testing them demonstrate that it can be utilized successfully. With all the excitement, it’s hard to remember that Blockchain is still in its infancy. There’s a chance that data science may be one of the industries that flourishes as technology advances and new ideas are introduced.