As a data engineer, it’s essential to understand how systems function in order to design data solutions that make the most efficient use of available resources. Data must align with core data quality principles, which means choosing a system architecture that best meets our specific needs.
I invite you to join me on a journey to explore system design and how it can be tailored to support modern data requirements. I am reading the book System Design Interview by Alex Xu, and I will share my notes here. By the end of this journey, we should be equipped to select the most effective architecture to handle Big Data workloads and ensure high-quality, scalable solutions.
Key Concepts:
- Domain Name System (DNS): a fundamental part of the internet that translates human-readable domain names (like google.com) into machine-readable IP addresses. It is a paid service provided by 3rd parties and not hosted by our servers.
- Internet Protocol (IP) Address: is a numerical label such as 192.0.2.1 that is assigned to a device connected to a computer network.
- Private IP: is an IP address reachable only between servers in the same network; however is unreachable over the internet
- HyperText Transfer Protocol (HTTP): is the foundation of the World Wide Web, and is used to load web pages using hypertext links
- JavaScript Object Notation (JSON): is a text format for storing and transporting data. JSON is “self-describing” and easy to understand.
Daniela Fernandez 