During the previous years, Google cloud initiated blockchain transaction history datasets for Bitcoin and Ethereum. Recently, the company introduced six more datasets that helps enable multi-chain meta-analyses and integration with record processing systems.
I’m very interested to quantify what’s happening so that we can see where the real legitimate use cases are for blockchain. So people can acknowledge that and then we can move to the next use case and develop out what these technologies are really appropriate for.
All of these five crypto assets(BCH, LTC, DASH, ZEC and DOGE) have similar implementations. This means their source code originates from Bitcoin. Ultimately, the sixth one is ETC which is based on Ethereum is the original blockchain. The datasets are updated every 24 hours through a common codebase which is the Blockchain ETL(Extract, Transform, Load) ingestion framework.
The Blockchain ETL ingestion framework enables real time streaming transactions for all blockchains. Google’s BigQuery data analytics platform initiated with Bitcoin and Ethereum last year. The Google Search Giant has a machine learning tool for searching patterns in transaction flows.
During this period developers were monitoring usage of software to build the next six datasets. Also, this Google search giant has a machine learning tool for searching patterns in transaction flows. This helps in providing basic information on how a crypto address is applicable.
The first terabyte of inquiries for these datasets are free each month with additional fee charged per byte or a flat $40,000 monthly rate for high-volume users.While blockchain data doesn’t include information about where a transaction occurs, Day is personally exploring how BigQuery ML might be leveraged to reveal transaction locations.
This is not some kind of dependency on government agency reporting. We have all the data, and we can pull metrics and and look at them and reason about them over time.