This dataset is part of a larger effort to make cryptocurrency data available in Google BigQuery through the Google Cloud Public Datasets program. The program is hosting a number of real-time cryptocurrency datasets, with plans to expand offerings to include additional distributed ledgers. You can find these datasets by searching for “crypto” in the GCP Marketplace. For analytics interoperability, Google has designed a unified schema that allows all Bitcoin-like datasets to share queries.
This public dataset is hosted in Google BigQuery and is included in BigQuery’s 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets.
What is BigQuery?
Google BigQuery makes it simple to query on-chain data in a simple, organized manner on the cloud using standard SQL syntax. You can think of it like a massive indexer that allows you to perform powerful data analysis. You are also able to perform the same or similar queries on multiple blockchains at once and compare them, or track cross-chain activity on interoperable tokens.
Some possibilities unlocked using Google BigQuery on the Polygon Dataset include the ability to:
Monitor gas costs over time
Monitor a smart contract’s calls and activity
Multi-Chain Analysis for SDKs like the Polygon SDK
Integrate with traditional financial record processing systems
Determine the most active/popular tokens, contracts, or applications on Polygon
Audit groups of transactions
Sample Queries to get started with Polygon Data on BigQuery:
You can find out the number of active addresses on Polygon by running this simple query.
# Calculate Active Monthly EOA's from Polygon Transactions
DATE(TIMESTAMP_TRUNC(block_timestamp, MONTH, "UTC")) AS month,
COUNT(DISTINCT from_address) AS active_addresses
GROUP BY month
ORDER BY month DESC
After running the query, you will get the results which can then be exported as CSV/to Google Sheets for further analysis. You can also proceed to use Google Data Studio to generate interactive visualizations based on this data, by clicking on the ‘Explore Data’ button.
Using Google Data Studio to Visualize Query Results
Example of using BigQuery for Polygon Datasets
Interested in learning more about how the data from these blockchains were brought into BigQuery? Looking for more ways to analyze the data? Check out the Google Cloud Big Data blog post and try the sample queries to get started.
Who made this happen?
We look forward to seeing how the vibrant developer community at Polygon uses this powerful platform to bring further utility to their Dapps!
Source : blog.polygon