Importance of SQL for Product Managers and some commonly used SQL queries

Product management involves steering your product in the right direction quickly. Data is a crucial component of decision-making, and conducting primary analysis yourself can significantly enhance your efficiency as a product manager.

Given that relational databases are still the most common types of databases, learning SQL (Structured Query Language) becomes crucial for PMs.

Relational databases such as MySQL, PostgreSQL, Oracle, and SQL Server are extensively used across industries. These databases store and manage vast amounts of critical data. Since SQL is the standard language for interacting with these databases, understanding SQL is essential for accessing and manipulating this data.

Why Should Product Managers Learn SQL?

1. They can independently query databases without constantly relying on data analysts or engineers, speeding up the process of data retrieval.

2. Understanding SQL enables better communication with data engineers, analysts, and developers, ensuring clear and precise data requirements.

3. Working knowledge of SQL helps PMs comprehend the limitations and possibilities of data retrieval, leading to more realistic expectations and effective collaboration.

SQL for Product Managers

While SQL allows you to read, insert, update, or delete data in relational databases, as a product manager, your primary focus will be on reading data as read queries in SQL will help you extract valuable data from relational databases.

Here are some of the most common read queries, along with examples:

1. SELECT Query

SELECT * 
FROM table_name;

SELECT * 
FROM users;

This query retrieves all columns and rows from the users table.

2. SELECT Specific Columns

You can specify which columns to retrieve by listing them after the SELECT keyword.

SELECT column1, column2, ...
FROM table_name;

SELECT first_name, last_name, email 
FROM users;

This query retrieves the first_name, last_name, and email columns from the users table.

3. WHERE Clause

The WHERE clause is used to filter records based on specific conditions.

SELECT *
FROM table_name 
WHERE condition;

SELECT * 
FROM users 
WHERE age > 25;

This query retrieves all columns for users who are older than 25.

4. LIMIT Clause

The LIMIT clause is used to specify the number of records to return.

SELECT * 
FROM table_name 
LIMIT number;

SELECT * FROM users LIMIT 10;

This query retrieves the first 10 rows from the users table.

5. DISTINCT Keyword

The DISTINCT keyword is used to return only distinct (different) values.

SELECT DISTINCT column_name
FROM table_name;

SELECT DISTINCT country 
FROM users;

This query retrieves the list of unique countries from the users table stored inside the country column.

6. COUNT Function

The COUNT function in SQL is used to count the number of rows in a table that match a specified condition. Here are a few examples to illustrate how it works:

Counting All Rows in a Table -

SELECT Count(*)
FROM table_name;

SELECT Count(*)
FROM users;

This query retrieves the count of rows from the users table.

Counting Rows with a Specific Condition -

SELECT Count (*)
FROM table_name 
WHERE condition;

SELECT * 
FROM users 
WHERE age > 25;

This query retrieves the count of rows from the users table where users have an age greater than 25.

7. SUM Function

The SUM() function in SQL is used to calculate the total sum of a numeric column.

SELECT SUM(column_name)
FROM table_name
WHERE condition;

SELECT SUM (total_sales)
FROM users; 

This query returns the sum of total_sales for all the records in the users table.

8. AVG Function

The AVG() function in SQL is used to calculate the average of a numeric column.

SELECT AVG(column_name)
FROM table_name
WHERE condition;

SELECT AVG (total_sales)
FROM users; 

This query returns the average of total_sales for all the records in the users table.

9. ORDER BY

It is used to sort the result set of a query by one or more columns. Sorting can be done in ascending order (default) or descending order.

SELECT *
FROM table_name
ORDER BY columnname;

SELECT *
FROM users
ORDER BY age;

This query returns all the records in the users table sorted in ascending order by age.

10. LIKE

is used to search for a specified pattern in a column. It is often used with WHERE clause to filter data based on partial matches. The LIKE operator can be used with two wildcard characters:

• % - Represents zero or more characters.

• _ - Represents a single character.

Here are some examples to illustrate how the LIKE operator works:

Example 1: Using % Wildcard

Suppose you have a table named users and you want to find all users whose names start with the letter 'A':

SELECT *
FROM users
WHERE name LIKE 'A%';

Example 2: Using _ Wildcard

To find all users whose names have 'B' as the second character:

SELECT *
FROM users
WHERE name LIKE '_B%';

SQL LIKE is case-insensitive in some databases like MySQL, but it is case-sensitive in others like PostgreSQL. For case-insensitive searches in PostgreSQL, you can use the ILIKE operator.