🚀 Complete Data Science Roadmap 2026

📍 Phase 3: SQL for Data Science

📖 Topic 1: SQL Basics — SELECT

SQL is one of the most important skills for a Data Scientist because real-world data is often stored in relational databases.

Before using Python, Machine Learning, or advanced analytics, you will frequently need to:

Retrieve data

Filter data

Combine tables

Aggregate information

Create datasets for analysis

Answer business questions

We'll start from the foundation: SELECT.

🔹 1. What Is SQL?

SQL stands for:

Structured Query Language

It is used to communicate with relational databases.

For example, a company might store:

Customers

customer_id | name  | city   | age
101         | Alice | Mumbai | 28
102         | Bob   | Pune   | 32
103         | Carol | Delhi  | 25

You can use SQL to retrieve specific information from this table.

🔹 2. What Is a Database?

A database is a structured system used to store and manage data.

A relational database stores information in tables.

For example:

Customers

Contains customer information.

Orders

Contains order information.

Products

Contains product information.

These tables can be related using common columns such as:

customer_id

This becomes extremely important when we learn JOINs.

🔹 3. What Is a Table?

A table consists of:

Rows

Each row generally represents one record.

Example: One customer

Columns

Each column represents an attribute.

Example: customer_id, name, city, age

So:

Row → Record

Column → Attribute

🔹 4. Your First SQL Query

The basic SQL query is:

SELECT *
FROM customers;

Let's break it down:

SELECT

Specifies what data you want.

*

Means: Select all columns.

FROM

Specifies the table from which you want the data.

customers

The table name.

So the query means:

Give me all columns from the customers table.

🔹 5. Selecting Specific Columns

You don't always need every column.

Suppose you only want:

Customer ID

Customer name

Use:

SELECT customer_id, name
FROM customers;

Result:

customer_id | name
101         | Alice
102         | Bob
103         | Carol

This is usually better than using SELECT * when you only need a few columns.

🔹 6. Selecting One Column

You can select a single column:

SELECT name
FROM customers;

Result:

name
Alice
Bob
Carol

🔹 7. Selecting Multiple Columns

Separate column names using commas:

SELECT name, city, age
FROM customers;

This returns only those three columns.

🔹 8. What Does * Mean?

The asterisk:

*

means: All columns.

Example:

SELECT *
FROM customers;

If the table has 10 columns, the query returns all 10.

However, in production environments, it is often better to explicitly specify the columns you need.

Instead of:

SELECT *
FROM customers;

prefer:

SELECT customer_id, name, city
FROM customers;

when those are the only fields required.

🔹 9. SQL Statements and Semicolon

SQL statements are commonly terminated with:

;

Example:

SELECT name
FROM customers;

The semicolon indicates the end of the SQL statement in many SQL environments.

🔹 10. SQL Is Declarative

This is an important concept.

When you write:

SELECT name
FROM customers;