Where Data and Web3 Meet
As we assume no prior knowledge of data or blockchain, this chapter introduces the basic concepts of both topics. A good understanding of these concepts is essential to tackle Web3 data science projects, as we will refer to them. A Web3 data science project tries to solve a business problem or unlock new value with data; it is an example of applied science. It has two main components, the data science ingredients and the blockchain ingredients, which we will cover in this chapter.
In the Exploring the data ingredients section, we will analyze the concept of data science, available data tools, and the general steps we will follow, and provide a gentle practical introduction to Python. In the Understanding the blockchain ingredients section, we will cover what blockchain is, its main characteristics, and why it is called the internet of value.
In the final part of this chapter, we will dive into some industry concepts and how to use them. We will also analyze challenges related to the quality and standardization of data and concepts, respectively. Lastly, we will briefly review the concept of APIs and describe the ones that we will be using throughout the book.
In this chapter, we will cover the following topics:
- What is a business data science project?
- What are data ingredients?
- Introducing the blockchain ingredients
- Approaching relevant industry metrics
- The challenges with data quality and standards
- Classifying the APIs
