SQL for Data Analytics

Name: SQL for Data Analytics
Rating: 4.4 (259 reviews)

Become an expert in SQL!

Created byTuan Vu

Last updated 6/2023

English

English [Auto],

What you'll learn

Become an expert in SQL and PostgreSQL
Write complex SQL queries with ease
Learn Advanced SQL concepts
Answer product or data questions using SQL and Data Analysis
Apply Data Analytics to make data-informed decisions
Replicate real-world situations and find actionable business insights
Create visualizations to present your insights
Ace the Advanced SQL job interview questions

Course content

7 sections • 46 lectures • 3h 24m total length

What is SQL?2:40
Course FAQs1:08
Setup with Mode2:39
Assignment: Introduce Yourself0:12

SQL Introduction2:42
Explore SQL fundamentals and learn to access and retrieve data in databases using SQL, illustrated with the Billboard Top 100 year end table and basic table concepts.
SELECT - FROM2:06
LIMIT0:56
Use limit clause to view first few rows of a table, avoiding loading entire dataset. Place limit at end of query and adjust from 10 to 20 rows.
WHERE1:20
SQL Introduction
Comparison Operators1:53
Filter data with the where clause using comparison operators, applying conditions like year greater or equal than 2011 and top five songs per year.
Logical Operators: AND, OR, NOT2:51
LIKE2:44
Apply the like operator to search patterns with % for multiple characters, _ for a single character, and use I like for case-insensitive results, including starts with or contains Taylor.
IN, NOT IN1:45
BETWEEN1:30
IS NULL1:08
ORDER BY3:17
Sort data using order by clause to arrange by artist name or year_rank, ascending or descending, and by multiple columns. Use where and limit to filter, and substitute column numbers.
Logical Operators

Introduction to Joins2:27
Why do we split data into separate tables?4:25
Inner Join8:52
Left and Right Join5:37
JOINs and Filtering3:57
JOINs and Aggregation9:12
Learn to use joins and aggregation in SQL for data analytics to build sales dashboards, analyze total sales by month, top accounts, and regional performance.
Full Outer Join6:47
UNION, UNION ALL3:31
Learn how to combine two data sets with union and union all, following rules for number of columns, similar data types, and column order, and understand how duplicates are handled.
Self-Join12:10
Master self-join and subjoined techniques in SQL to compare rows within the same table, using aliases for hierarchical relationships and time-series patterns, such as orders within 30 days.
SQL Joins
Solution: SQL Join Assignment0:13

Introduction to WINDOW Functions6:03
SUM: Compute a cumulative sum4:37
Learn to compute a cumulative sum with window functions in sql for data analytics, using over, partition, order by, and window frame clause to produce running totals by date.
ROW_NUMBER, PARTITION BY5:16
RANK, DENSE_RANK7:28
learn how row_number, rank, and dense_rank compute ordered rankings within a window partition and identify the top 10 accounts by region based on sales quantity.
Aggregates in Window Functions2:44
Window Frame7:02
Explore how to use the window frame clause to compute running totals, moving averages, and min/max values across a partition.
LAG, LEAD2:17
Explore using lag and lead to compare sales quantities against previous or next rows, compute day over day growth, and analyze two day prior trends in SQL for data analytics.
Assignment: SQL Window Functions0:27
Solution: SQL Window Functions assignment38:55
Attached is the solution for the SQL Window Functions Assignment. For visualization questions, you can use anything you want, the preferred way is to use Mode’s Dashboard.

Requirements

No programming experience needed - I'll teach you everything you need to know
A Mac or PC computer with access to the internet

Description

Welcome to SQL for Data Analytics!

There are literally thousands of SQL courses online, but most of them don’t prepare you for using it in the real world.

In this course, instead of just learning about the basic fundamentals of SQL, I will teach you how to use SQL and data to develop your Data Analytics mindset. Together, we will learn how to apply SQL and Data Analysis to real-life business use cases, to draw insights from data in order to make data-informed decisions. We will also learn about the advanced concept in SQL like Self-join and Window Analytics Functions to solve complex business problems.

We even go further to present and communicate that insight effectively with interactive visualization dashboard.

This course requires absolutely no programming experience.

By the end of this course, you will be well equipped to pass all of the SQL interviews questions in the data world: whether you are looking for a job as a data scientist, data analyst, or data engineer.

Feel free to look through the preview videos of this course to see if it's a good fit for you!

Remember I offer a 30-day money-back guarantee, so you can join me for an entire month, risk-free, and decide whether to keep going or not.

I'll see you inside the course!

Best,

Tuan Vu

Who this course is for:

Beginners who wants to learn about SQL
Beginners who wants to learn about Data Analysis
Beginners who wants to learn about Data Science
Beginner developers curious about Data Science
Intermediate developers wants to learn Advanced SQL concepts
Intermediate SQL developers wants to advance their career
People who wants to prepare for SQL Job Interview questions
Beginners who want to prepare for Data Science interview questions
Beginners who want to prepare for Data Engineer interview questions
Beginners who wants to learn about PostgreSQL

SQL for Data Analytics

What you'll learn

Explore related topics

Course content

Introduction4 lectures • 7min

Basic SQL Fundamentals11 lectures • 22min

SQL Aggregations8 lectures • 22min

SQL Joins10 lectures • 57min

SQL Subqueries & Common Table Expression3 lectures • 21min

Advanced: SQL Window Functions9 lectures • 1hr 15min

Conclusion1 lecture • 1min

Requirements

Description

Who this course is for: