Database Fundamentals

The database is your workstation, and you are the architect and keeper of the data as a data engineer. So, it’s essential to thoroughly understand databases, how they work, and all of their subtleties. Beginning with the fundamental foundational concepts, we will gradually move on to more complicated features of databases in this chapter before dissecting these principles via the context of a data engineering interview.

This chapter will walk you through various topics, whether you’re a novice just entering this industry or a seasoned professional trying to brush up on your knowledge. These include database types, normalization, and indexing fundamentals. In a series of common interview questions and responses, we will put the lessons gained to use. Your technical communication abilities will be improved in this segment, which is a crucial component of any data engineering interview. The chapter will conclude with a brief summary to help you remember...

Must-know foundational database concepts

In this section, we will create the groundwork for your understanding of databases, which is a crucial component for any data engineer. We start with the fundamentals, such as comprehending the many types of databases, the normalization tenets, and the idea of indexing. These foundational elements will serve as the starting point for your exploration of the more complex world of data engineering. This part is the starting point for a more in-depth investigation of database systems, whether you are a beginner or an experienced professional reviewing the fundamentals. Let’s begin by strengthening your fundamental database knowledge.

Relational databases

A relational database utilizes a relational model to store structured data into tables. Tables are collections of rows and columns. Each row in the table represents a single record of information, while each column represents attributes or fields. The following screenshot is an example...

Must-know advanced database concepts

After going over the basics of databases, it’s time to delve into more complicated subjects that are essential tools in the toolbox of a data engineer. We’ll summarize various advanced concepts, including triggers, ACID characteristics, and constraints. To guarantee data integrity, consistency, and responsiveness in a database system, each aspect is crucial. Understanding them will improve your conceptual knowledge and your capacity to create and maintain sophisticated database systems.

Remember that this part is not intended to teach you how to do these things from scratch but rather to provide you with a brief overview and prepare you for the kinds of questions and subjects frequently used in interviews for data engineering jobs. Let’s clarify things and increase your knowledge of databases.

Constraints

Constraints are rules that are set up to enforce properties in a database. Without constraints, your data will be...

Technical interview questions

The focus of this chapter’s final portion shifts to how our database knowledge can be used in technical interviews. Here, we list often-asked interview questions for data engineering positions.

This portion serves two purposes: to assess your comprehension of the fundamental and advanced database concepts presented in prior sections and to improve your ability to communicate your solutions. You can understand the underlying ideas and create a systematic approach to problem-solving because each question is supported with a thorough answer and explanation.

By actively participating in these interview questions, you will strengthen your understanding of database foundations and gain more confidence in your ability to reply to technical questions during job interviews:

• Question 1: What is a primary key, and why is it important in a relational database?

  Answer: A primary key is the unique identifier for each row in a table. It cannot be...

Summary

In this chapter, we covered both foundational and advanced database concepts essential for data engineers. We explored different types of databases, normalization, indexing, NoSQL databases, OLTP/OLAP systems, and triggers. Additionally, we provided technical interview questions to test your knowledge and problem-solving skills.

In the next chapter, we will dive into essential SQL for data engineers, focusing on the indispensable SQL skills required for efficient data manipulation and management within databases. Let’s continue our journey by mastering essential SQL techniques for data engineering.