This lesson introduces you to the exciting world of Web3 data analytics. You'll learn about essential tools and techniques used to explore on-chain data, understand user behavior, and gain valuable insights into decentralized applications (dApps) and blockchain networks.
Web3 data, unlike traditional data, is fundamentally transparent and publicly accessible on blockchains. Every transaction, interaction with a smart contract, and wallet activity is recorded on-chain. This provides an unprecedented opportunity to analyze user behavior, understand network activity, and track the performance of dApps.
Key Data Sources:
Several tools are designed for Web3 data analysis, each with its strengths:
Even without advanced tools, you can perform basic analysis.
Example using Etherscan:
1. Find a Transaction: Go to Etherscan.io and paste a transaction hash.
2. Analyze Details: Examine the sender, receiver, the tokens transferred (if any), and the gas fees paid.
3. Explore Addresses: Click on sender and receiver addresses to see their transaction histories.
Explore advanced insights, examples, and bonus exercises to deepen understanding.
Welcome back to the fascinating world of Web3 data analytics! You've already laid the groundwork by understanding key data sources, popular tools, and basic querying techniques. This session builds on that foundation, offering deeper dives, practical exercises, and real-world applications to elevate your analytical skills. Prepare to uncover even more hidden treasures within the blockchain.
While understanding transaction volume and active users is crucial, Web3 data offers much more depth. Let's delve into some less explored areas and alternative perspectives:
Using Etherscan or another block explorer, identify a few "whale" transactions (high-value transactions). Analyze:
Using Dune Analytics (or similar tool), construct a query to analyze the retention rate of users on a specific dApp (e.g., Uniswap, OpenSea). Define user cohorts based on the week they first interacted with the app, and track how many of those users return in subsequent weeks. (Hint: you'll likely use date functions, grouping, and aggregations)
Web3 data analytics is transforming businesses and investment decisions. Here's how it's making an impact:
Ready to push your skills further? Try these more complex tasks:
The journey of a Web3 data analyst never ends! Here are some avenues for continued exploration:
Go to Etherscan.io. Choose a recent transaction from the Ethereum network. Analyze the transaction details, including the sender, receiver, gas used, and any tokens transferred. Try to understand what happened in the transaction.
Visit Dune Analytics and browse through some of the pre-built dashboards. Try to understand the metrics being displayed and how they relate to the dApp or blockchain being analyzed. Pick one dashboard and describe what information you learned about the project.
Imagine you have identified a wallet that interacts frequently with a specific DeFi protocol. Using available tools (Etherscan, Dune, etc.) and information, what are some questions you could ask about this wallet's activity? (e.g., How much did they invest? Are they consistently profitable? What assets do they hold?)
Imagine you are researching a new DeFi protocol. Use Etherscan and Dune Analytics (or similar tools) to analyze the protocol's transaction volume, active users, and TVL. Create a short report summarizing your findings, highlighting any notable trends or insights.
Prepare for the next lesson by researching different DeFi protocols and identifying key metrics used to assess their performance. Try to familiarize yourself with basic SQL concepts, as you will need them for querying data in Dune Analytics.
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