Basic English simplifies SQL concepts - Lesson 2

If you speak basic English, writing SQL becomes effortless

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SELECT these columns or all columns FROM this table WHERE this condition is true or false but I don’t want to see all thousands or millions of results, just LIMIT is to first 10, 20, 50 or 100 data records.

But I want you to ORDER BY the results from smallest to largest (A to Z) aka Ascending (ASC) or from largest to smallest Descending (DESC).

Since we spend a lot of money on music for different countries, I want to GROUP BY the total amount we spent in each country for music.

You can further refine your query to be more precise and adaptable to different conditions by using SQL command

• IN: to check is a value exist in a specific list

• LIKE: to search for patterns in text

• BETWEEN: to filter values within a range

• NOT: to exclude specific values or conditions

If you are still confused do not stress — we will use the Chinook database to explain everything above in examples that is easy to follow.

SELECT and FROM: the core of SQL

Every SQL query begins with SELECT and FROM. Think of these as the what and where of your query.

Example

Imagine you are looking at the Tracks table and want to list all track names:

SELECT Name 
FROM Tracks;     

This query tells SQL: Find the Name column in the Tracks table

Output (partial)

Name 
---------------- 
For Those About to Rock 
Put The Finger On You 
Let's Get It Up 
...

By default, SQL returns every row in the table—whether there are 10 or 10,000 rows.

SELECT * : Retrieving All Data

In SQL, the asterisk (*) is a wildcard that represents all columns in a table. When you want to select every column from a table, you simply use SELECT *.

Example

Suppose you want to view every piece of information about tracks from the Tracks table:

SELECT * FROM Tracks;

This query returns every column and every row from the Tracks table.

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WHERE: Filtering Your Data

The WHERE clause is your filter. It helps you narrow down the results to only those that meet specific conditions.

Example

Suppose you want tracks with a Milliseconds value greater than 300,000 (about 5 minutes):

SELECT Name, Milliseconds 
FROM Tracks 
WHERE Milliseconds > 300000;

This query returns only tracks longer than 5 minutes.

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LIMIT: Keep It Short and Sweet

Sometimes, you don’t need all the data. LIMIT helps you control how many rows are returned.

Example

Let’s retrieve the first 5 tracks:

SELECT Name 
FROM Tracks 
LIMIT 5;

Output

Name 
---------------- 
For Those About to Rock 
Put The Finger On You 
Let's Get It Up 
Inject the Venom 
Snowballed

---

ORDER BY: Sorting Matters

ORDER BY arranges your data. By default, it sorts in ascending order, but you can specify DESC for descending.

Example

List the top 5 longest tracks:

SELECT Name, Milliseconds 
FROM Tracks 
ORDER BY Milliseconds DESC 
LIMIT 5;

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GROUP BY: Aggregating Your Data

GROUP BY lets you summarize data. Pair it with aggregate functions like COUNT, SUM, or AVG.

Example

Count how many tracks each album contains:

SELECT AlbumId, COUNT(*) AS TrackCount 
FROM Tracks 
GROUP BY AlbumId;

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IN and NOT: Specifying Multiple Values

Use IN to filter data based on a list of values. Add NOT to exclude those values.

Example

Find all tracks from artists with IDs 1, 3, or 5:

SELECT Name 
FROM Tracks 
WHERE ArtistId IN (1, 3, 5);

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BETWEEN: Working with Ranges

BETWEEN is ideal for specifying ranges, whether dates, numbers, or strings.

Example

Find tracks with Milliseconds between 200,000 and 300,000:

SELECT Name, Milliseconds 
FROM Tracks 
WHERE Milliseconds BETWEEN 200000 AND 300000;

---

NULL: Handling Missing Values

In SQL, NULL represents missing data. Use IS NULL or IS NOT NULL to filter for or exclude these rows.

Example

Find tracks with missing composer information:

SELECT Name 
FROM Tracks 
WHERE Composer IS NULL;

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Wrapping Up

Mastering these foundational SQL commands, SELECT, FROM, WHERE, LIMIT, ORDER BY, GROUP BY, IN, NOT, BETWEEN, and NULL is your first step to becoming a confident data analyst. Each command is like a puzzle piece that helps you construct meaningful queries.

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