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Google wants to make all the blockchain data associated with Ethereum easily accessible to people. It is doing this by making all the Ethereum datasets available through BigQuery, the scalable and highly scalable data warehouse of Google oriented towards data analysts
People can query data tables for free
One of the most beneficial aspects of this development for the data of the scientists is that they can immerse themselves in the data for free. When using the Python library of BigQuery, you can use Kernel, a free browser-based coding platform available on Kaggle, a well-known data science website. The Kernel tool allows people to work with the Ethereum data tables through SQL queries.
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Ethereum and Smart Contracts
Ethereum is a platform for the use of tokens to carry out transactions known as smart contracts. In simple terms, smart contracts strengthen relationships with cryptographic code and work exactly as their creators dictate. For example, an individual could enter into an intelligent contract that sends a certain amount of Ether, the cryptocurrency associated with Ethereum, on a given date and does so on a repetitive basis. Other smart contracts only work if a minimum number of people agree to enter.
To demonstrate what an Ethereum query could communicate to people through BigQuery, Google sought to determine the most popular smart contract associated with Ethereum. They found out that it was connected to a game called CryptoKitties and that the transaction took place more than 2.3 million times.
An expansion of what is already available
The software exists that allows you to check the balance in an Ethereum portfolio or to find out the status of a transaction. However, what Google offers is different because it gives access to all the data stored on the Ethereum blockchain.
This progress could stimulate greater possibilities for Big Data scientists who are interested in analyzing the blockchain but previously could lack resources. This way of using big data could also help people understand that there are many ways to use blockchain technology that does not refer to cryptocurrencies. For example, a company could create a fully automated supply chain management tool or provide up-to-date company information to stakeholders in real time. The data views of Google's Ethereum represent data extracted from the Ethereum registry every day, so data scientists are certain of updated data.
The company has published another example related to the previously mentioned game CryptoKitties in which they performed a query that informed them how many users have had at least 10 so-called cryptoKitties creatures in the game.
If data scientists wanted to use data differently, they could use a similar query that shows the most popular ways that people use Ethereum and how they change over time. Alternatively, they could trace peaks of activity and try to find out the reasons behind those flashes of abnormal use.
Google explains its big data blockchain offer
A Google blog post gives more details about why the company decided to give people access to the Ethereum data this way. For beginners, API endpoints for aggregate Ethereum data did not exist before Google made this move.
In the blog post, the writer suggests an 'activities based on the architecture of Ethereum for a portion of his operations could use a large data query to conclude it's time for an update of the idea of u200b u200b u200b u0026lt; ;architecture. You can also use a query to find out the transaction frequencies between particular portfolio addresses.
In addition, BigQuery can provide insights on the functions of particular smart contracts, even if users do not have the source codes for such contracts. So if a company that is considering starting to use a certain type of smart contract employs a data scientist, it could gather data that shows whether those contracts are on the agenda or are still emerging.
Other blockchain data may be imminent
While discussing the process of updating Ethereum's blockchain data in BigQuery, Google briefly mentions the company to welcome other types of blockchain information for its system, as well as other contributors. Since Google is such a respected name in the technology industry in general, people may soon see more data on BigQuery.
Likewise, people working in areas such as data science and machine learning may begin to investigate with the Google tool, then develop their own platforms or coordinate with others in a team effort to do so. .
If that happens, the blockchain data becomes readily available, opening up countless possibilities for people interested in data science to work with specialized platforms for their needs.
the Author
Contributed by: Kayla Matthews, a technology writer and blogger who covers big data topics for websites like Productivity Bytes, CloudTweaks, SandHill and VMblog.
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