I previously wrote about how to use BigQuery to analyse Ethereum datasets. This is quick and easy for datasets that already have event tables thanks to the hard work of the Blockchain BigQuery team, but what if you want to analyse events that aren’t already broken out into their own tables? There is a global event table, bigquery-public-data.crypto\_ethereum.logs, but event data is in its raw format there - not easy to query on.

Today, Vitalik published a thoughtful piece on ENS name registration fees, and mechanisms for making the namespace more sustainable in the long run. It makes some excellent points, and moves away from a simple Harberger Tax model to a more nuanced model that takes into account some essential demands of decentralised naming systems, such as the need for stability in how a name resolves.

While Dune Analytics has rightly gotten a lot of positive attention recently for providing an easy-to-use platform for doing analytics over Ethereum datasets, you may not know that Google also provides a comprehensive dataset of Ethereum data on its large-scale analytics querying platform, BigQuery.