Data Analysis SQL Fundamentals
Through detailed lectures and hands-on practice on the core elements of SQL, we will create a solid foundation for you to grow into a SQL analysis expert.
This course is prepared for Basic Learners.
What you will learn!
Different types of joins and join operation mechanisms
Understanding Group by and Aggregation Functions and Transforming Dataset Levels
Freely handle Date, Timestamp, and Interval
Different types of Analytic SQL and how to use them
Various tips to keep in mind when applying Analytic SQL in practice
Understanding subqueries and their various uses
The first step to becoming a SQL analysis expert! 💪
Build your fundamentals with detailed lectures and practical training.
Accessing data
The most basic technology, SQL.
Most corporate data is stored in RDBMS, and SQL is the most basic technology for accessing data. Therefore, the core of corporate data analysis starts with utilizing SQL.
However, it is difficult to find a data analyst who can freely use SQL for corporate data analysis. If you approach SQL only from the grammar and functional aspects when learning it, you will be frustrated when you encounter analysis requirements that include slightly difficult data processing and changes to the set level in real life.
Analytical SQL ,
If you want to do it right?
To be good at analytical SQL, you must have the ability to freely process and create original data into the level of the desired set. To do this, you must develop the ability to write SQL while understanding various types of joins, Group by, aggregate functions, and the mechanism by which Analytic SQL works. And you must be able to acquire this through a lot of practice.
Data Analysis SQL Fundamentals Course is ✅
Data Analysis SQL Fundamentals is Part 1 of a series of lectures designed to help you grow into a SQL analysis expert. This lecture is structured so that you can acquire the core contents and mechanisms of JOIN, Group by, aggregate functions, and Analytic SQL through detailed lectures and practice.
Follow-up series: SQL data analysis through various cases
In Part 2 of the lecture, 'SQL Data Analysis through Various Cases', we will perform various types of sales analysis, order analysis, website access and usage analysis, and website performance analysis using SQL based on Google Analytics-type data sets. We will meet you with a rich set of analysis topics, such as session and DAU/WAU/MAU, traffic source analysis by device/ad channel, landing page analysis, bounce rate and exit rate aggregation, RFM analysis, retention rate, and funnel analysis.
A key weapon for real-world analysis ,
Analytic SQL!
Analytic SQL, also known as Window Function, has played a major role in making SQL the center of corporate data analysis with its convenient and flexible analysis usability and advanced statistical functions. In this lecture, we will explain almost all of the Analytic SQL frequently used in practice .
In particular, we have prepared various visual materials to help you understand Analytic SQL more easily. We will also help you master Analytic SQL through considerations when applying it and various types of practice SQL.
Features of this course ✨
Rich description of core SQL operation mechanisms
We provide a detailed explanation of how different types of joins work, as well as how Group by and Analytic SQL work.
A variety of practice problems combining core understanding and advanced content
The main SQL exercises consist of live coding, and various practice problems are prepared so that you can learn in-depth content while understanding the core.
Analytic SQL - I can't explain it in more detail than this
We will explain in detail how the main components of Analytic SQL, Partition, Sort, and Window, work with visual aids. We will also inform you of errors that are easy to overlook when using Analytic SQL and how to resolve them.
Bonus! 100 pages of lecture material provided
We provide a 100-page lecture textbook, practice SQL code, and datasets so that you can easily understand the content on your own.
Practice environment
Check it out 💻
PostgreSQL is used as the practice environment DBMS and DBeaver is used as the SQL editor.
PostgreSQL is an open source DBMS that is provided free of charge and has stability, performance, and, above all, rich SQL support functions. It satisfies the Ansi SQL standard and has various SQL functions and analytical functions, so it is widely used not only online but also as an analytical DBMS.
DBeaver Community Edition is free, but it has better features, faster performance, and stability than most commercial SQL Editors. DBeaver supports various DBMSs such as PostgreSQL, MySQL, and Oracle.
📢 Instructions for downloading lecture materials
- The lecture materials (PDF), practice SQL code, and data can be downloaded from the [Download lecture materials and practice code] class in Section 0: Introduction to the lecture and setting up the practice environment.
Q&A 💡
Q. Can someone who knows nothing about SQL take the course?
This lecture is for those who have a brief basic knowledge of SQL. The lecture proceeds on the assumption that you know about SELECT, WHERE clause, and ORDER BY, so the lecture starts with JOIN. If you are new to SQL, I recommend that you watch a short SQL basic introduction lecture on YouTube or Inflearn that is about 1 to 2 hours long. The pre-course knowledge is explained in more detail at about 5 minutes of the lecture introduction video.
Q. Do I need to take this course first to take the "SQL Data Analysis with Various Case Studies" course that will be released later?
Unfortunately, the SQL data analysis course that will be released later, with various cases, assumes that you have some knowledge of the content explained in this course. For prerequisite knowledge for taking the SQL data analysis course with various cases, please refer to the course introduction in Section 0 of the course curriculum and the course selection guide for those who have not taken the Data Analysis SQL Fundamentals course in advance and refer to it when selecting a course.
Letters from knowledge sharers 💌
In the field of data analysis, I have been thinking about how to improve both data analysis and SQL skills at the same time for a long time (and that is why I am losing my mind...).
In order to catch these two rabbits, we plan to release two series of lectures that will continuously improve your skills by implementing various types of practical data analysis indicators and various analysis requirements desired in the field using SQL.
Firstly, the 'Data Analysis SQL Fundamentals' course being released this time is designed to help you solidify your SQL capabilities through detailed explanations of the basic mechanisms that make up SQL and various practical exercises.
In particular, we will explain Analytic SQL, the core SQL weapon for data analysis, in detail from A to Z, so you will be able to have solid confidence in Analytic SQL wherever you are.
I created this course so that it can be a valuable time for you to improve your SQL skills. Questions are always welcome and I hope to see you in class.
Well then, I'll quickly disappear to finish the lecture 'SQL Data Analysis with Various Case Studies' that will be released soon.
thank you
Recommended for
these people!
Who is this course right for?
Those who want to improve their SQL skills
Anyone who wants to build solid analytical SQL skills
Data Scientists and Data Analysts Leveraging SQL
Data engineers who need to perform data processing/extraction/refinement based on SQL to create tables for analysis or marts
Those who have learned basic SQL grammar but still have difficulty applying SQL to analysis tasks
Need to know before starting?
SQL grammar (Select, Where clause, etc.) in the introductory course
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Curriculum
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76 lectures ∙ (14hr 7min)
are provided.