How leveraging blockchain data can be a revolutionary act

The legitimacy of cryptocurrencies is under constant threat from bad actors. For example, wash trading is a big problem and widespread in NFT sales. One high-profile case was exposed in a popular market, proving that 94% of $2 billion traded was a wash trade.

how did you know that? The NFT analytics site examined blockchain data over eight days. It’s not small, but it’s a high-value service that the industry takes for granted to build trust.

Analytics and data aggregation companies are therefore poised to become mainstays of the space by providing key information about what is really happening on the blockchain. It’s no surprise that regulators question the burgeoning technology.

Business applications will also proliferate, as the big move from Chainlink (LINK) shows. Last year, the company announced a partnership with news agency Associated Press to make its dataset available on major blockchains. There, data can be used to automate key processes that occur on the chain.

Whether it’s informing the market of a call for election competition, triggering on-chain transactions when a company’s quarterly earnings are announced, or augmenting the NFT’s appearance based on real-world events, this one One partnership has great reach. When applied across the world of business across multiple industries, it can lead to significant changes in data usage.

good information

Well-matched and well-analyzed data has the potential to weed out risky companies and individuals and thwart their malicious goals. In theory, blockchain data is publicly available. It means that everyone can do their own work. In practice, this is not realistic. This is because the average vigilante company, or even one just starting out in analytics, lacks the technology to create massive data sets in a scalable way at an accelerated pace.

Knowing exactly what you want in data terms is a big hurdle. Therefore, bespoke platforms will need to work with industry players, and more specifically developers, to extract useful data on a scale not yet seen in the blockchain industry. Aggregation and analysis face a steep learning curve in the early stages.

Apply data holistically

For business applications, private blockchains dominate. Customized structured data can be processed accordingly into private datasets. This is commercially useful. If companies paid a lot to pull data based on very specific requests, especially given that these data sets continue to grow and remain highly relevant due to the nature of blockchain. , you want to protect your data. Additionally, access rights can be sold to other companies under license agreements.

When it comes to entities looking to siphon data for the public good, there is scope to build datasets that enable crowdsourced analysis. The crypto industry desperately needs this. We don’t have enough funds to expose wash trading or other malicious activity. Now we rely on the actions of a zealous minority. Adequate and universal access to clean data could stimulate the emergence of public institutions to help cryptocurrency become a self-regulating field.

I just scratched the surface. Insurance is a huge consumer of data as it informs the entire business model as brokers need to know how to claim competitive yet profitable premiums. And Chainlink is leading the charge here as well. Last year, it signed a deal with Arbol, an insurance startup. Arbol provides crop insurance for farmers and businesses to provide decentralized weather data. In this case, smart contracts can trigger payments depending on weather condition data.

data reconciliation

Traditional businesses face many problems when selling their data to third parties, but with cryptocurrencies this is less of a concern as everything is transparent. However, most projects in the web3 space is not fully decentralized, leading to decisions about whether or not to take certain data off-chain.

The advantage of a comprehensive data aggregation protocol is the ability to reconcile on-chain and off-chain data. Businesses can customize data links to work. For most projects, having only half the data visible is fine. Because we only need to move the data on-chain to make the necessary decisions.

Because while the Ethereum Virtual Machine (EVM) chain dominates the space, there are chains like Solana that create cutting-edge solutions.

The text in blockchain data itself needs to be structured in a very specific way for a chain like Solana, as the whole technology behind it is different. Additionally, the high transaction-per-second rate offered by Solana means that the database is much more expansive than most other chains, from genesis block to real-time. Solana has hundreds of thousands of transactions per second.

If your database is chock-full of data, it may not always be useful to others. Given the sheer volume of transactions, it becomes very difficult for data cleaning service providers to structure the data in a way that removes noise from the clean part. Many of the transactions are meaningless and of no value for analysis.

For centralized chains, the aggregation and subsequent analysis of data can help build trust in an environment where the entity itself controls validators, thereby extending political control over key players across the ecosystem. you can exercise. Once trust is lost, it cannot be easily regained, so blocking out the noise and seeing what is happening with on-chain transactions is invaluable. This is one of the reasons blockchain data is so important and has the potential to dramatically change how we interact with cryptocurrencies.

Guest post by Tom Tirman of IQ Protocol

Tom Tirman is CEO of IQ Protocol. IQ Protocol is his leading NFT rental solution that allows games and other platforms to wrap their digital assets and rent them out to users who want to play and earn money. Prior to Crypto, Tim studied law at one of the leading technical universities in Eastern Europe and continued his studies at the Stockholm School of Economics. Also in his spare time he spearheads PARSIQ, his aggregator of web3 data.

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