There are lots of ways Blockchain data can help Data Scientist in general, and here are some of those use cases,
- Ensuring Trust
Every single data recorded in Blockchain are trustworthy because they have gone through a verification process which very much ensures its quality. Blockchain technology also supports transparency in almost every activities and transactions so that no vandalism will take place or else it will be traced.
Previously, Lenovo revealed this use case of blockchain technology to detect fraud/false forms and documents. Not only that, PC giants used blockchain technology to validate paper documents which were encoded with digital signatures. Then, digital signatures are processed by the computes and the authenticity of the document if verified through a blockchain record and keeps everything updated.
2. Preventing malicious activities
Consensus algorithm is the key to verify transactions in Blockchain which makes it almost impossible for a block to pose a threat to the entire data network. If there is any node in the chain that acts differently will be easily detectable and fixed from the network. Since the network is distributed network, it is almost impossible for a single party or a person to generate enough computational power to alter the validation and allow unwanted data in the network, which makes it the safest of all. In order to alter blockchain rules, majority of nodes needs to be pooled together to create consensus. Therefore, it is almost impossible for a single bad actor to achieve.
3. Predictive Analysis
In predictive analysis, Data Scientist base on big data to determine solid accuracy and forecasting. Blockchain data can be analyzed to reveal valuable insights, trends and as such can be used to predict future outcomes. Another beneficial point is that blockchain provides structured data gathered from individuals or individual IOT devices.
And due to the distributed data, that blockchain provides and huge computation power that it provides, data scientist can take extensive predictive analysis task in a small place.
4. Real time data analysis
Several banks and tech innovators are exploring blockchain because it works faster than the general databases irrespective of its geographic barriers. Likewise, organizations that needs real time data analysis of data in tremendous scale can call it on blockchain enabled system to achieve. With blockchain, Banks and other organization can observe changes in data in real time making it possible and easy to take quick decisions.
5. Manage Data Sharing
In such manner, Data gotten from data studies can be stored in a blockchain network. This way, project groups don’t repeat data analysis done by other group and wrongfully use data that’s already been used. Additionally, a blockchain stage can help Data scientist adapt their work, probably by trading analysis outcome stored on the stage.