Things I wish I knew about Data Engineering — Data Lifecyle

As a data engineer, continuous learning is key to staying ahead in this ever-evolving field. Recently, I’ve been diving into the Fundamentals of Data Engineering by Joe Reis and Matt Housley. This book has been a fantastic resource, even for someone with my level of experience. It has broadened my horizons and introduced me to new concepts that are crucial for anyone transitioning into data engineering. One of the standout topics is the data life cycle, which I believe is essential knowledge for all aspiring data engineers.

The Data Engineering Life Cycle: From Ingestion to Insights

The role of a data engineer is more critical than ever. Data engineers are the backbone of any data-centric organization, ensuring that data is collected, stored, and made accessible for analysis. Let’s take a closer look at the data engineering life cycle and the key stages involved.

1. Data Ingestion

The first step in the data engineering life cycle is data ingestion. This involves collecting data from various sources, such as databases, APIs, and streaming services. Data can come in different formats, including structured, semi-structured, and unstructured data. The goal is to gather all relevant data and bring it into a centralized…