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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