Blockchain and Big Data is one of the top emerging technology tips to revolutionize several industries, radically changing the way businesses and organizations are run. One might assume that these technologies are mutually exclusive - each forging a unique path and implemented independently of each other.
But it would be off the mark.
Blockchain - such as data science - is gradually changing the way some of the industry operates. And while the science of data focuses on the utilization of data for proper administration, Ensuring blockchain believe the data to maintain a ledger of decentralization.
The question is, Is there a place these two concepts intercept?
What will be achieved when the two simultaneously applied this technology?
Simply put, how can blockchain interrupt the data science?
To answer this question, it is helpful to gain a better understanding of Blockchain and Data Sciences apart from each other.
If big is the quantity, Maria Weinberger of Janexter said blockchain is the quality. It follows the understanding that blockchain focused on data validation when science data or big data involves making predictions of large amounts of data.
Blockchain has brought a new way to manage and operate data - no longer in perspective where all data centers should be brought together but in a decentralized way in which the data can be analyzed directly on the edge of the individual devices. Blockchain integrated with other advanced technologies, such as cloud solutions, artificial intelligence (AI) and the Internet of Things (IOT).
Furthermore, the data generated through the technology validated blockchain come complete structured and coupled with the fact that change as we mentioned earlier. Another important area in which data generated blockchain be the impetus for large data is data integrity since blockchain explores the origin of data despite its chain related.
There are at least five specific ways blockchain the data can help scientists data in general.
- Ensuring Trust (Data Integrity)
Data recorded on blockchain reliable because they must have gone through a verification process that ensures quality. It also provides for transparency, because of the activities and transactions that occur on the network can be traced blockchain.
Last year, Lenovo showed off case blockchain use of this technology to detect false documents and forms. PC giant blockchain use technology to validate the physical documents are encoded with a digital signature. The digital signature is processed by the computer and the authenticity of the document is verified through the records blockchain.
Often, data integrity is confirmed when the details of the origin and the interaction of the data blocks stored in blockchain and automatically verified (or validated) before it can be acted upon.
- Prevent Malicious Activity
Because blockchain using consensus algorithm to authenticate the transaction, it is impossible for the unit to pose a threat to the data network. A node (or units) began acting normally can be easily identified and removed from the network.
Because the network is so distributed, it makes it almost impossible for a single party to produce enough computing power to change the validation criteria and allows the unwanted data in the system. To change the rules blockchain, the majority of nodes must be pooled together to create a consensus. This would not be possible for bad actors to achieve.
- Make a prediction (predictive analysis)
Blockchain data, such as data type, can be analyzed to reveal valuable insights into behavior, trends and thus can be used to predict future outcomes. What is more, blockchain provide structured data collected from an individual or an individual device.
In predictive analytics, data base of scientists on large data sets to determine with good accuracy the results of social activities such as customer preferences, customer lifetime value, dynamic pricing, and the churn rate associated with the business. It is, however, not limited to business insights for almost every event can be predicted with the correct data analysis whether it is social or markers investment sentiment.
And because of the distributed nature blockchain and massive computing power available through the data that scientists even smaller organizations can perform the tasks of comprehensive predictive analysis. This data scientists can use the computing power of several thousand computers connected to the network blockchain as cloud-based services for analyzing social outcomes on a scale that would not be otherwise possible.
- Real-Time Data Analysis
As has been exhibited in the financial and payment systems, brand blockchain for real-time cross-border transactions. Some banks and innovator fintech now exploring blockchain because it affords fast - in fact, the real-time - the completion of a large number regardless of geographical barriers.
In the same way, organizations that require real-time analysis of data on a large scale can call blockchain-enabled system to achieve. With blockchain, banks and other organizations can observe data changes in real-time allowing for rapid decision - whether to block suspicious transactions or track any abnormal activity.
- Managing the Data Sharing
In this case, the data obtained from the study data can be stored in the network blockchain. In this way, the project team did not repeat the data analysis was done by another team or reuse the data that has been used wrongfully. Also, a platform can help scientists blockchain data monetize their work, possibly by causing trade analysis results are stored on the platform.
Conclusion:
Blockchain, as already noted, in a nascent stage although it may not appear so because of the hype of technology has got in a short time. One would expect that as a mature technology, and there is more innovation around it, more concrete use cases will be identified and explored - the science of data into one area that will benefit from this.
That being said, some challenges have been raised about its impact in the sciences, especially the data in the big data that requires a very large amount of data to be handled. One of the concerns is that the application blockchain in this case would be very costly to pursue. This is because the storage of data on a blockchain expensive compared to the traditional way. Blocks are dealing with a relatively small amount of data compared to the large volume of data collected per second for large data analysis tasks and other data.
How to evolve to address this issue and continue to disrupt space science data will be because it is very interesting, as we have seen blockchain, the technology has great potential to change how we manage and use data.
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