Learn SQL for Data Analysis: Beginner to Advanced Guide

 SQL (Structured Query Language) is one of the most important skills for us, data people. So in this article + video, get the necessary SQL skills you need for Data Analysis work.

Step 0: Install MySQL software

I am using the FREE MySQL Community Edition software to learn & practice SQL at home. You can get it from here.

If you have any other database software available (such as SQL Server or Oracle), you can use them to follow this tutorial.

 

Step 1: Import Awesome Chocolates Dataset

You need some data to practice SQL. So I prepared a sample dataset for a fictional (but yummy) company called Awesome Chocolates.

Download the .SQL file from here.

After you have the file, 

0. Open MySQL Workbench, login if necessary
1. Click on the “server administration” tab (see illustration, click to expand)
2. Click on “Data Import/Restore”
3. Select the option “Import from self-contained file”
4. Specify the path of the downloaded awesome-chocolates-data.sql file
5. Start import

 

At the end of these steps, your MySQL should have the awesome chocolates database. Congratulations

You can see this from “Schemas” tab on the workbench

 

Using SQL Server?

You can also use SQL Server to practice SQL. If you are using SQL Server Management Console, then follow below steps to import the data.

 

1. Download this SQL Server Backup file
2. Unzip the file
3. Open SSMS & right click on the databases and chose “Restore Database” option. Follow the steps on that screen using below screenshots.

 

Step 2: Learn SQL for Data Analysis with this video

Everything is ready. Time to learn SQL.

I made an hour long tutorial to explain all the necessary SQL concepts for you. In this video, you will learn:

• How to use SELECT statement to answer business questions
• Working with WHERE clause
• Using AND, OR, NOT and combining them to create complex queries.
• Sorting query results using ORDER BY
• Combining data from two or more tables using JOINS
• Creating reports with GROUP BY
• More than 50 example queries, tips and ideas

-- Select everything from sales table

select * from sales;

-- Show just a few columns from sales table

select SaleDate, Amount, Customers from sales;

select Amount, Customers, GeoID from sales;

-- Adding a calculated column with SQL

Select SaleDate, Amount, Boxes, Amount / boxes  from sales;

-- Naming a field with AS in SQL

Select SaleDate, Amount, Boxes, Amount / boxes as 'Amount per box'  from sales;

-- Using WHERE Clause in SQL

select * from sales

where amount > 10000;

-- Showing sales data where amount is greater than 10,000 by descending order

select * from sales

where amount > 10000

order by amount desc;

-- Showing sales data where geography is g1 by product ID &

-- descending order of amounts

select * from sales

where geoid='g1'

order by PID, Amount desc;

-- Working with dates in SQL

Select * from sales

where amount > 10000 and SaleDate >= '2022-01-01';

-- Using year() function to select all data in a specific year

select SaleDate, Amount from sales

where amount > 10000 and year(SaleDate) = 2022

order by amount desc;

-- BETWEEN condition in SQL with < & > operators

select * from sales

where boxes >0 and boxes <=50;

-- Using the between operator in SQL

select * from sales

where boxes between 0 and 50;

-- Using weekday() function in SQL

select SaleDate, Amount, Boxes, weekday(SaleDate) as 'Day of week'

from sales

where weekday(SaleDate) = 4;

-- Working with People table

select * from people;

-- OR operator in SQL

select * from people

where team = 'Delish' or team = 'Jucies';

-- IN operator in SQL

select * from people

where team in ('Delish','Jucies');

-- LIKE operator in SQL

select * from people

where salesperson like 'B%';

select * from people

where salesperson like '%B%';

select * from sales;

-- Using CASE to create branching logic in SQL

select SaleDate, Amount,

case when amount < 1000 then 'Under 1k'

when amount < 5000 then 'Under 5k'

                when amount < 10000 then 'Under 10k'

else '10k or more'

end as 'Amount category'

from sales;

-- GROUP BY in SQL

select team, count(*) from people

group by team

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Homework Problems

INTERMEDIATE PROBLEMS
You need to combine various concepts covered in the video to solve these

1. Print details of shipments (sales) where amounts are > 2,000 and boxes are <100?
2. How many shipments (sales) each of the sales persons had in the month of January 2022?
3. Which product sells more boxes? Milk Bars or Eclairs?
4. Which product sold more boxes in the first 7 days of February 2022? Milk Bars or Eclairs?
5. Which shipments had under 100 customers & under 100 boxes? Did any of them occur on Wednesday?

HARD PROBLEMS
These require concepts not covered in the video

1. What are the names of salespersons who had at least one shipment (sale) in the first 7 days of January 2022?
2. Which salespersons did not make any shipments in the first 7 days of January 2022?
3. How many times we shipped more than 1,000 boxes in each month?
4. Did we ship at least one box of ‘After Nines’ to ‘New Zealand’ on all the months?
5. India or Australia? Who buys more chocolate boxes on a monthly basis?

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Solutions (cheating)

INTERMEDIATE PROBLEMS:

— 1. Print details of shipments (sales) where amounts are > 2,000 and boxes are <100?

select * from sales where amount > 2000 and boxes < 100;

— 2. How many shipments (sales) each of the sales persons had in the month of January 2022?

select p.Salesperson, count(*) as ‘Shipment Count’
from sales s
join people p on s.spid = p.spid
where SaleDate between ‘2022-1-1’ and ‘2022-1-31’
group by p.Salesperson;

— 3. Which product sells more boxes? Milk Bars or Eclairs?

select pr.product, sum(boxes) as ‘Total Boxes’
from sales s
join products pr on s.pid = pr.pid
where pr.Product in (‘Milk Bars’, ‘Eclairs’)
group by pr.product;

— 4. Which product sold more boxes in the first 7 days of February 2022? Milk Bars or Eclairs?

select pr.product, sum(boxes) as ‘Total Boxes’
from sales s
join products pr on s.pid = pr.pid
where pr.Product in (‘Milk Bars’, ‘Eclairs’)
and s.saledate between ‘2022-2-1’ and ‘2022-2-7’
group by pr.product;

— 5. Which shipments had under 100 customers & under 100 boxes? Did any of them occur on Wednesday?

select * from sales
where customers < 100 and boxes < 100;

select *,
case when weekday(saledate)=2 then ‘Wednesday Shipment’
else ”
end as ‘W Shipment’
from sales
where customers < 100 and boxes < 100;

 

HARD PROBLEMS:

— What are the names of salespersons who had at least one shipment (sale) in the first 7 days of January 2022?

select distinct p.Salesperson
from sales s
join people p on p.spid = s.SPID
where s.SaleDate between ‘2022-01-01’ and ‘2022-01-07’;

— Which salespersons did not make any shipments in the first 7 days of January 2022?

select p.salesperson
from people p
where p.spid not in
(select distinct s.spid from sales s where s.SaleDate between ‘2022-01-01’ and ‘2022-01-07’);

— How many times we shipped more than 1,000 boxes in each month?

select year(saledate) ‘Year’, month(saledate) ‘Month’, count(*) ‘Times we shipped 1k boxes’
from sales
where boxes>1000
group by year(saledate), month(saledate)
order by year(saledate), month(saledate);

— Did we ship at least one box of ‘After Nines’ to ‘New Zealand’ on all the months?

set @product_name = ‘After Nines’;
set @country_name = ‘New Zealand’;

select year(saledate) ‘Year’, month(saledate) ‘Month’,
if(sum(boxes)>1, ‘Yes’,’No’) ‘Status’
from sales s
join products pr on pr.PID = s.PID
join geo g on g.GeoID=s.GeoID
where pr.Product = @product_name and g.Geo = @country_name
group by year(saledate), month(saledate)
order by year(saledate), month(saledate);

— India or Australia? Who buys more chocolate boxes on a monthly basis?

select year(saledate) ‘Year’, month(saledate) ‘Month’,
sum(CASE WHEN g.geo=’India’ = 1 THEN boxes ELSE 0 END) ‘India Boxes’,
sum(CASE WHEN g.geo=’Australia’ = 1 THEN boxes ELSE 0 END) ‘Australia Boxes’
from sales s
join geo g on g.GeoID=s.GeoID
group by year(saledate), month(saledate)
order by year(saledate), month(saledate);

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One Book Setup all file 

Second Book All Commands SQL Advance