Google’s Data Analytics Platform BigQuery Now Provides Insights Into Ethereum Blockchain Data

Google’s big data analytics platform BigQuery has recently added Ethereum for the analysis of smart contracts, the search giant said in an official blog post last week. With the help of BigQuery, it will now be possible to explore all of the Ethereum's historical data.

The ETL project for Ethereum available of GitHub comprises the entire source data that can be extracted from the blockchain network and sourced into BigQuery. The Ethereum’s software already consists of APIs which allows checking the wallet balances; however, the API endpoints are not accessible for all the data that is stored the blockchain.

BigQuery’s ‘OLAP features’ overcome the limitations of API endpoints by allowing to view the blockchain data in aggregate. This aggregated data visualization allows prioritizing on the core structure of the Ethereum network whenever an upgrade is required.

Google said: ”A visualization like this ... is useful for making business decisions, such as prioritizing improvements to the Ethereum architecture itself (is the system running close to capacity and due for an upgrade?) to balance sheet adjustments (how quickly can a wallet be rebalanced?).”

The BigQuery data analytics system which runs on the Google Cloud platform does multiple tasks like pulling data from Ethereum ledger on daily basis, as well as information regarding smart contract transactions; synchronizing the Ethereum blockchain with computers running on Parity; and it "de-normalizes and stores date-partitioned data to BigQuery for easy and cost-effective exploration.”

BigQuery also provides information like contract tables and dataset transactions giving insights into the most used smart contracts based on the number of transactions. BigQuery data showed that Cryptokitties has the most smart contract transactions on the Ethereum network.

One can also discover CryptoKitties like similar games by deploying the Jaccard similarity coefficient that allows to directly compare the similarity and diversity of sample sets using a JavaScript UDF.

Additionally, Google’s data analytics platform also allows measuring a token by time window like the number of token transfers for a given token on a daily basis.