Web3 Analytics 101: Async Course
An open course that teaches students how to understand and analyze blockchain data using SQL.
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An open course that teaches students how to understand and analyze blockchain data using SQL.
Last updated
Was this helpful?
This course is designed for students who want to answer questions with data, provide context to protocol growth and change, and understand what is happening behind the scenes.
The goal of this course is to take interested students and teach them the requisite knowledge to be a data analyst in web3. Our goal is that students emerge from the course with an intermediate level of knowledge. We define that as being able to confidently tackle challenges with tools such as , , , , etc. While a "beginner" analyst may be limited to high-level overviews, an "intermediate" analyst is able to push beyond surface-level analysis, extracting insights from curiosity-directed exploration.
In short, a successful course will produce a cohort of talented analysts creating great content and actively competing in bounty programs.
We will explore Ethereum data throughout this course as it has the most robust tooling and data available. Core concepts can be applied across a range of EVM-compatible chains and alternate blockchains.
Please register using the .
The following is intended to set expectations about the content of this course, while the content covered will go into more depth than what is listed.
We will be compiling vetted resources that students can dive into, on their own time, to get up to speed with the main topics that this course covers: blockchains and crypto, data analysis using SQL, working in web3, etc.
Finally, find some MetricsDAO resources here:
Establishing foundational knowledge
Blockchain, distilled, and what is Ethereum?
Data
What tools are out there?
Accessing curated datasets and using SQL to explore blockchain data.
Why do this kind of work?
The analytics ecosystem and work2earn.
Expand technical abilities with live use-cases.
Available data
Exploratory analysis and understanding what we're looking at.
Observing trends with high-level aggregations.
Comparing Ethereum transactions in data tables to block explorers.
Domain knowledge - understanding your subject
Exploring data through visual representations
Introducing intermediate SQL techniques and diving into (more) raw transaction data.
SQL Aggregations - benefits and pitfalls
Data, uncurated
Moving beyond ez_
tables working with JSON message objects.
SQL syntax: Dune Engine V2 vs. V1
Column-oriented data
Using Dune abstractions
Cross-chain analysis
Creating professional outputs
Breaking into web3 data.
We will primarily use and . I suggest signing up for both websites (for free) and familiarizing yourself with them!
Expert session led by Dune Wizard .
In the closing session of the course, , and discuss: