Blockchain data requires analytics to understand network activity. Every network is unique which makes them hard to compare.
Chainwalking transforms blockchain data into a universal data model that powers Flipside’s Business Intelligence, enabling projects to better understand their networks and benchmark performance against others.
First we characterize a blockchain’s schema, which can be thought of as an outline of all the key definitions needed to extract data from a particular blockchain. We then build a parser based on the agreed upon schema. A parser is a small amount of code that defines the blockchain data in terms of its height, or its total number of blocks, and its content per block.
Flipside runs the parser in our infrastructure which automatically extracts the blockchain’s data, ‘walking’ through the chain one block at a time until it reaches its maximum height. The height will increase as new blocks are added to the chain, which means we are continuously extracting new data and ingesting it in our warehouse.
There is no standard for how blockchain data is structured, which means the raw data from one blockchain doesn’t look anything like the raw data from another. Using our Universal Data Model (UDM), our data engineering team transforms all of the data into a standard format. The UDM we’ve designed is incredibly flexible, can be applied to any chain, and means our models will work with minimal adjustments and validation.
Our Data Science team analyzes the resulting data to show who holds supply, and what those key stakeholders are doing on-chain. This labeled representation can then be sliced to access relevant insights, for instance to show: who users are; who holds how much; what users are doing; which users come back; and when key events occur.Technical documentation