Advanced SQL for Data Engineering

Mastering SQL Database Management and SQL Query Optimization for High-Performance Data Engineering
Advanced SQL for Data Engineering
File Size :
952.21 MB
Total length :
2h 23m



365 Careers


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Advanced SQL for Data Engineering

What you’ll learn

Execute Database Manipulation
Manage DateTime in SQL
Handle Complex Data Types
Master Advanced Query Techniques
Optimize Databases

Advanced SQL for Data Engineering


Fundamental SQL Knowledge
Basic Database Understanding
Familiarity with Relational Databases


Dive deep into the world of SQL with the Advanced SQL for Data Engineering course. This course is tailored for individuals aiming to sharpen their SQL skills and grasp advanced database design concepts, essential for numerous roles in today’s data-driven industry.The course is structured into eight comprehensive sections. It begins with setting up the environment and an overview of relational databases to establish the groundwork for more advanced SQL topics. You will be introduced to SQL syntax, as well as Data Definition Language (DDL), Data Manipulation Language (DML), Data Query Language (DQL), and Data Control Language (DCL).The subsequent sections progress systematically through the manipulation of databases, managing and manipulating DateTime in SQL, handling complex data types, and exploring advanced query techniques. You will master essential SQL statements such as CREATE, ALTER, INSERT, UPDATE, DELETE, MERGE, and DROP.Then you will dive into the subtleties of DateTime types, timezones, and intervals, and get hands-on experience with ENUMs. Ranges, and nested data. Each topic is designed to equip you with advanced techniques for managing, querying, and manipulating databases.After that you will explore advanced query techniques with a focus on OVER, various types of JOINS, CASE, CONCAT, and the powerful Recursive Common Table Expressions (CTEs). These concepts will hone your skills in complex data querying, a pivotal aspect of data engineering.The sixth section deals with optimizing data structures and introduces the concept of data normalization in SQL. You will learn the theory and practical application of data normalization, as well as the STAR schema and Snowflake model, both essential in designing efficient databases.Section seven delves into performance and control, where you will master stored procedures, User-Defined Functions (UDFs), temporary tables, materialized views, and transactions. These concepts enhance your capabilities to manage and optimize databases for peak performance.The final section allows you to put all the knowledge you’ve gained into practice with a series of challenging exercises. These practical tasks are designed to cement your understanding of the topics covered and prepare you for real-world scenarios.By the end of the Advanced SQL for Data Engineering course, you will be proficient in SQL’s advanced features and capable of designing, managing, and optimizing databases effectively. Whether you’re a budding data engineer or an experienced professional seeking to enhance your skills, this course has you covered!


Section 1: Setting up the environment and overview of relational databases

Lecture 1 Introduction to the course

Lecture 2 Coure GitHub repository

Lecture 3 Setting up the environment

Lecture 4 An overview of relational databases

Lecture 5 DDL, DML, DQL, DCL

Lecture 6 SQL syntax

Section 2: Manipulating databases: Mastering essential SQL statements

Lecture 7 Intro SQL statements

Lecture 8 CREATE

Lecture 9 ALTER

Lecture 10 INSERT

Lecture 11 UPDATE

Lecture 12 DELETE

Lecture 13 MERGE

Lecture 14 DROP

Section 3: Timing is everything: managing and manipulating DateTime in SQL

Lecture 15 DateTime intro

Lecture 16 Different DateTime types

Lecture 17 Timezones

Lecture 18 Intervals

Section 4: Complex data types: ENUMs, ARRAYs, Ranges, and Nested data in SQL

Lecture 19 ENUM

Lecture 20 ARRAYs

Lecture 21 RANGE

Lecture 22 Nested data

Section 5: Advanced query techniques: exploring OVER, JOINS, CASE and more in SQL

Lecture 23 OVER

Lecture 24 CROSS JOIN



Lecture 27 COALESCE

Lecture 28 CASE

Lecture 29 CONCAT

Lecture 30 Recursive CTE

Lecture 31 Recursive CTE – second part

Section 6: Optimizing data structures: The art and science of data normalization in SQL

Lecture 32 Data normatlization (1/3)

Lecture 33 Data normatlization (2/3)

Lecture 34 Data normatlization (3/3)

Lecture 35 STAR schema Snowflake

Section 7: Performance and control: Mastering stored procedures, temporary tables

Lecture 36 Stored procedures and UDFs (1/3)

Lecture 37 Stored procedures and UDFs (2/3)

Lecture 38 Stored procedures and UDFs (3/3)

Lecture 39 Temp table

Lecture 40 Materialized view

Lecture 41 Transactions

Lecture 42 SQL structures

Section 8: Practical tasks

Lecture 43 Question 1

Lecture 44 Question 2

Lecture 45 Question 3

Lecture 46 Question 4

Aspiring Data Engineers,Data Professionals,Database Administrators

Course Information:

Udemy | English | 2h 23m | 952.21 MB
Created by: 365 Careers

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