Can Blockchain Change The Game Of Data Analytics And Data Science?

Can Blockchain Change The Game Of Data Analytics And Data Science?
Blockchain has been causing ripples across major industries and verticals in the recent couple of years. We are seeing the future potential of blockchain technology that is scaling beyond just cryptocurrencies and trading.

It is only natural that Blockchain is going to have a huge impact on Data Analytics, another field that has been booming and seems to continue in the same trajectory for the foreseeable future.

However, very little research has been done on the implications of blockchain on Data Science or the potential of Data Science in Blockchain.

While Blockchain is about validating data and data science is about predictions and patterns, they are linked together by the fact that they both use algorithms to control interactions between various data points.

Blockchain in Big Data Analytics

Big Data has traditionally been a very centralized method where we had to collate data from various sources and bring it together in one place. Blockchain, considering its decentralized nature can potentially allow analysis of data to happen at the origin nodes of individual sources.

Also, considering that all data parsed through blockchain is validated across networks in a fool proof manner, the data integrity is ensured. This can be a game changer for analytics.

With the digital age creating so many new data points and making data more accessible than ever, the need for diving into depth with advanced analytics has been realized by businesses around the world. However, the data is still not organized and it takes a very long time to bring them together to make sense of it.

The other key challenge in Big Data remains data security. Centralized systems historically have been known for their vulnerability for leaks and hacks.

A decentralized infrastructure can address both of the above challenges enabling data scientists to build a robust infrastructure to build a predictive data model and also giving rise to new possibilities for more real time analysis.

Can Blockchain Enhance Data Science?

Blockchain can address some of the key aspects of Data Science and Analytics.

Data Security & Encoding:

The smart contracts ensure that no transaction can be reversed or hidden. The complex mathematical algorithms that form the base of Blockchain are built to encrypt every single transaction on the ledger.

Origin Tracing & Integrity:

Blockchain technology is known for enabling P2P relationships. With blockchain technology, the ledgers can be transparent channels where the data flowing through it is validated and every stakeholder involved in the process is made accountable and accessible. This also enables the data to be of higher quality than what was possible with traditional methods.

Summing Up

Data science itself is fairly new and advancing in recent years. Blockchain Technology, as advanced as it seems, is still at what is believed to be a very nascent stage. We have been seeing an increasing interest in data being moved to the cloud and it is only a matter of time when businesses will want it to be moved to decentralized networks.

On the other hand, blockchain’s network and server requirements are still not addressed and data analytics can be very heavy on the network, considering the volume of data collected for analysis. With very small volumes of data stored in blocks, we need viable solutions to make sure data analysis in blockchain is possible at scale.

At Pyramidion, we have been working with clients globally on some exciting blockchain projects. These projects are being led by visionaries, who are looking to change how the world functions, for good. Being at the forefront of innovation, where we see the best minds working on new technologies, ICOs and protocols, we strongly believe it is only a matter of time before the challenges are addressed and Blockchain starts being a great asset to another rapidly growing field like Data Science and Data Analytics.

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Trunomi

Trunomi offers an award-winning and innovative technology platform that gives companies unprecedented ways to interact with customer personal data; using a revolutionary consent-based data sharing platform; backed by multiple patent filings.

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But laborious processes can often end in a “bulk approval” to save time and check an audit box instead of accurately reviewing access rights to ensure the right business outcomes. RadiantOne’s AI-driven approach will be a paradigm shift in the way people work, forever transforming and streamlining the usually time-consuming UAR process down to days and minutes instead of months. “Historically, user access reviews are a highly manual process–a ‘necessary evil’ within security practices. This approach not only creates fatigue for the team but also introduces a considerable amount of risk,” says Dr. John Pritchard, Chief Product Officer at Radiant Logic. “While this may work in the short term to satisfy auditor requirements, the company’s assets are never truly protected. There is also still the risk that something may be overlooked, or someone within the business has retained access to something they shouldn’t. With RadiantOne AI and AIDA, existing IAM and IGA processes can be automated and simplified for overworked teams trying to comb through mountains of user access data to make the right decisions to protect their organizations.” With RadiantOne AI, conducting a user access review becomes as easy as following AIDA’s guidance. Using the power of large language models to drive advanced data correlation, contextualization and analysis, combined with an intuitive data visualization dashboard, AIDA will reinvent the user access review ritual. Based on an organization's proprietary data, the fully guided UAR experience will allow reviewers to interact and pose questions to AIDA using natural human language, like “where does this access come from?” or “show me who else has these access rights?” AIDA will highlight any potential user access risks, offer expert insight, and suggest remediations or access modifications based on an organization’s policies. 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Click-button remediation: Based on the insights and recommendations from AIDA, reviewers can approve or revoke access or atypical rights individually or take bulk approval/rejection actions with the click of a button. Data into the hands of business owners: Put relevant, risk-based identity data insights into the hands of business users in the language they understand to make it a breeze to adhere to compliance policies. “User access reviews with AIDA are just the beginning,” comments Joe Sander, Radiant Logic’s CEO. “Using RadiantOne’s AI engine, we see potential to revolutionize identity data management, governance, risk, compliance and cybersecurity processes by removing complexity as a roadblock. 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