Summary
As a summary of the first chapter, we've learned the fundamental knowledge we need as data engineers. Here are some key takeaways from this chapter. First, data doesn't stay in one place. Data moves from one place to another, called the data life cycle. We also understand that data in a big organization is mostly in silos, and we can solve these data silos using the concepts of a data warehouse and data lake.
As someone who has started to look into data engineer roles, you may be a little bit lost. The role of data engineers may vary. The key takeaway is not to be confused about the broad expectation in the market. First, you should focus on the core and then expand as you get more and more experience from the core. In this chapter, we've learned what the core for a data engineer is. At the end of the chapter, we learned some of the key concepts. There are three key concepts as a data engineer that you need to be familiar with. These concepts are ETL, big data, and distributed systems
In the next chapter, we will visit GCP, a cloud platform provided by Google that has a lot of services to help us as data engineers. We want to understand its preposition and what the services are that are relevant to big data, and lastly, we will start using the GCP console.
Now let's put the knowledge from this chapter into practice.