Extracting Insights from Blockchain Data – Part 2: Filtered & Cleaned Data

In the first part of this series, we discussed how permissionless blockchains generate new data every time someone interacts with them. Raw data is often obscure and human-unreadable but can nevertheless lead to high-level insights. In this second part, we’ll take a look at smart contract blockchains, specifically EVM-compatible (Ethereum Virtual Machine) blockchains, and how one can translate raw data into cleaned and filtered data that allows for more complex and protocol-specific insights.

A smart contract is a computer program designed to execute contract terms automatically when specific conditions are met. These programs are useful for automating and streamlining various transactions and processes, including token trading, NFT transactions, lending tokens on decentralized money markets, and more. Smart contracts are typically written in high-level programming languages like Solidity or Vyper. Upon deployment, the high-level instructions are compiled into executable bytecode, which is then deployed on the blockchain and associated with a unique address. This process ensures that the smart contract is immutable and secure, as it is stored on a decentralized network and can only be modified according to the rules set forth in the contract's code.