Preface
The advent of Web3 has ushered in a trove of data, characterized by its distinctive properties, giving rise to novel concepts and breathing new life into established ones. Within the expansive Web3 ecosystem, data assumes diverse forms, stored across multiple platforms and formats, ranging from on-chain transactional data to independent news aggregators, oracles, and social networks. In essence, Web3 is a continuous generator of data directly or indirectly related to its ecosystem.
Web3, with its inherent characteristics, has unlocked value on various fronts. Decentralization has demonstrated that businesses without central authorities are possible. Trustless interactions have driven coordination between entities, facilitating smooth exchanges of goods and services over the blockchain, even among strangers and without intermediaries. This has resulted in value transfers reaching remote corners of the world at minimal costs, fostering direct connections between artists and collectors and facilitating crowdfunding by directly supporting product developers, among a myriad of other applications.
However, one aspect of Web3 that remains relatively unexplored, yet holds immense value to unlock, is transparency. Transparency fosters reliance, a cornerstone for mass adoption. A significant milestone for the industry will be achieved when ordinary individuals seamlessly engage with it, grounded in trust due to accessible and verifiable information. To fully realize the potential of transparency, many Web3 data scientists and analysts, equipped with the requisite skills, conceptual knowledge, tools, and a profound understanding of the data and business landscape, are needed. This is what this book aims to do – empower you to evolve into Web3 data specialists capable of understanding and extracting value from data.
The book is structured into three parts. The first section covers foundational concepts necessary to execute data analysis tasks. You will gain insights into on-chain data, learn to access and extract insights, explore sources of relevant off-chain data, and navigate potential obstacles. Additionally, two domains that generate vast amounts of data, namely NFTs and DeFi, are examined in depth, each presenting its own set of business rules and technical concepts.
The second part of the book shifts focus to machine learning use cases utilizing Web3 data. We have curated practical cases that data scientists, whether freelancers or employed professionals, may encounter in their work.
The Appendix addresses the question, what should we do with the knowledge acquired? It provides guidance on navigating the decentralized work landscape, understanding industry expectations for prospective data employees, and identifying the soft and hard skills necessary for success. In order to offer a glimpse into the future of the industry, we have engaged with Web3 data leaders who share their experiences, perspectives, and visions. The intent of this part is to shorten the time required to find jobs or other ways to contribute in the industry.
The benefits of decentralization, trustless interactions, and transparency in trade cannot be ignored, and that is why the industry continues to grow year by year, unlocking new use cases and creating new jobs. The purpose of this book is to contribute to the understanding of the data that Web3 generates so that you can be prepared to shape the next era of the internet.
