CF

SQL for Data Engineers

1h 51m
English
Paid

SQL is the foundation for working with relational databases. If you plan to work in the field of Data Engineering, knowledge of SQL is not just a plus but a necessity. That's why we created this course: "SQL for Data Engineers". It will provide you with the essential skills for effective database management—from data extraction and analysis to executing complex queries and operations that you will encounter daily.

Course Overview

This course is designed to equip data engineers with in-depth SQL skills. Below we've outlined the key competencies you will gain.

Introduction to Database Management and SQL

Get acquainted with Database Management Systems (DBMS) and the role of SQL in data engineering. Understand how relational databases store, manage, and process large volumes of data.

Practice with the Chinook Database and Tool Setup

You will start working with real data using the Chinook Database, an educational database that helps you master key SQL concepts. We will set up SQLite and DBeaver - necessary tools for managing databases and writing queries.

SQL Basics: DDL and DML

You will delve into the fundamental sections of SQL - Data Definition Language (DDL) and Data Manipulation Language (DML). Learn how to create, modify, and manage tables and records: insert, update, and delete data.

Advanced Queries: SELECT, Grouping, and Joins

In the next stage, you will master advanced techniques for working with SELECT queries, aggregate functions, and JOINs. These skills are essential for working with multiple tables and extracting analytically valuable information.

Transaction Management and Data Integrity

You will study the Transaction Control Language (TCL) and understand how to maintain data integrity and reliability in working with DBMS.

Common Table Expressions and Subqueries

Learn to simplify complex SQL queries using CTE (Common Table Expressions) and subqueries, making your code more readable and maintainable.

Window Functions

In a separate four-part module, you will discover window functions: aggregate, ranking, and analytics. These allow you to perform calculations across rows with maximum flexibility.

Query Optimization and Indexing

At the end of the course, you will learn to optimize SQL queries and use indexes to improve performance. Special attention is given to practices in SQLite, but the principles apply to any relational DBMS.

About the Author: Andreas Kretz

Andreas Kretz thumbnail

Andreas Kretz is a German data engineer and one of the most widely followed independent voices on data engineering as a career discipline. He runs the Plumbers of Data Science brand and has been publishing tutorial material continuously since the field consolidated around the modern lake-house stack (Spark, Kafka, Snowflake, Databricks, Airflow).

His CourseFlix listing is the largest single-author catalog under this source — over thirty courses spanning data-pipeline construction, streaming architectures, the cloud-native data stack on AWS / Azure / GCP, the Python and Scala tooling that dominates the field, and the soft-skills / career side of breaking into data engineering. Material is paid and aimed at engineers transitioning into data work or already-working data engineers picking up specific tools.

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#1: Introduction
All Course Lessons (16)
#Lesson TitleDurationAccess
1
Introduction Demo
02:05
2
Database Management Systems & SQL
03:50
3
The Chinook Database
03:04
4
SQLite Installation
07:03
5
Dbeaver Installation
04:09
6
Data Types in SQLite
06:16
7
DML & DDL
15:07
8
Select Statements
06:04
9
Grouping & Aggregation
10:13
10
Joins
10:06
11
TCP Transaction Control Language
06:43
12
Common Table Expressions & Subqueries
10:27
13
Window Functions 1: Concept & Syntax
05:01
14
Window Functions 2: Aggregate Functions
07:25
15
Window Functions 3: Ranking Functions
06:06
16
Window Functions 4: Analytical Functions
07:21
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Books

Read Book SQL for Data Engineers

#TitleTypeOpen
1SQL_For_Data_Engineers_Cheat_Sheet PDF
2Query Optimization PDF
3Indexing best practices PDF

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Frequently asked questions

What prerequisites should I have before taking this course?
Before enrolling in this course, you should have a basic understanding of databases and general programming concepts. Familiarity with any programming language will be helpful, although not mandatory. The course is focused on SQL and relational databases, so prior experience in these areas, while beneficial, is not required as the course starts with introductory topics.
What projects or practical exercises will I work on?
In the course, you will work with the Chinook Database, which is an educational database designed to help you practice SQL concepts. You will use it to perform tasks such as creating tables, running SELECT queries, and executing joins and aggregate functions. This hands-on experience is designed to simulate real-world data engineering tasks.
Who is the target audience for this course?
This course is targeted at aspiring data engineers and professionals who want to strengthen their SQL skills. It is suitable for individuals who plan to work with relational databases in data engineering roles, as well as those who wish to enhance their ability to manage and manipulate large datasets using SQL.
How does the course depth compare to other SQL courses?
The course offers an in-depth exploration of SQL, covering both basic and advanced topics. Unlike some introductory courses, this one goes beyond basics by delving into advanced queries, including grouping, joins, and window functions. It is tailored for those seeking a comprehensive understanding of SQL for data engineering tasks.
What specific tools or platforms will I learn to use?
You will learn to use SQLite and DBeaver in this course. SQLite is used for database management and executing SQL queries, while DBeaver serves as a database management tool. These platforms are integral for hands-on practice with the Chinook Database and understanding SQL's application in real-world scenarios.
What topics are not covered in this course?
The course does not cover non-relational databases or SQL dialects specific to other database systems like PostgreSQL or MySQL. It focuses on SQL concepts applicable to relational databases, specifically using SQLite. Advanced database administration and performance optimization are also beyond its scope.
How can the skills learned in this course benefit my career?
The skills acquired in this course are foundational for any data engineering role. Mastery of SQL enables you to handle database management, data extraction, and complex querying—skills that are highly valued in data-driven industries. These competencies also serve as a stepping stone for learning other data-related technologies and techniques.