The `SELECT` statement is used to query and retrieve data from a database. It allows you to specify which columns and rows you want to fetch.

The SELECT statement in MySQL is the cornerstone of data retrieval, a powerful command that extracts precise information from vast databases with surgical accuracy, enabling analysts to query millions of rows in milliseconds and transform raw tables into actionable intelligence.

It begins with SELECT followed by column names specific fields like name, revenue, or * for all—then FROM to specify the source table, allowing extraction from single or multiple joined tables. The WHERE clause filters rows by conditions such as price > 1000 or region = ‘Newyork’, dramatically reducing result sets to only relevant data.

In lecture terms, SELECT is not just fetching data—it’s interrogating reality: “Show me the top 10 highest-spending customers in Q4 who haven’t ordered in 30 days.” It powers dashboards, reports, APIs, and machine learning pipelines, scaling from a single query to real-time analytics on petabyte warehouses. Master it, and you control the database’s narrative.

The `SELECT` statement is powerful and can be combined with various clauses like `WHERE`, `ORDER BY`, `GROUP BY`, and more to refine your queries.

Basic Syntax:

SELECT column1, column2 FROM table_name;

`column1, column2`: Specify the columns you want to retrieve. Use `*` to select all columns.

– `table_name`: The name of the table from which to retrieve data.

Examples:

1. **Select All Columns**

   SELECT * FROM employees;

2. **Select Specific Columns**:

   SELECT name, age FROM employees;

3. **Filtering Results with WHERE**:

   SELECT * FROM employees WHERE age > 30;

4. **Ordering Results with ORDER BY**:

   SELECT * FROM employees ORDER BY name ASC;

MODULE X

HAVING vs. WHERE in MySQL

Use `WHERE` for filtering rows before aggregation and `HAVING` for filtering aggregated results after `GROUP BY`.

`WHERE` Clause’

– Used to filter records before any groupings are made.

– Applicable to individual rows in a table.

– Cannot be used with aggregate functions (like `SUM`, `COUNT`, etc.) directly.

*Example

SELECT * FROM employees WHERE age > 30;

`HAVING` Clause’

– Used to filter records after groupings are made.

– Applicable to aggregated results.

– Often used with `GROUP BY` to filter groups based on aggregate values.

Example

SELECT department, COUNT(*) AS employee_count 

FROM employees 

GROUP BY department 

HAVING COUNT(*) > 10;

MODULE XX

This concise overview provides a quick reference to using `LIMIT` and `ALIASING` in MySQL queries for effective data retrieval and manipulation

LIMIT` + ALIASING`

Limits in MySQL

‘LIMIT` Clause’  It is used to restrict the number of rows returned by a query. The syntax is `LIMIT [offset,] row_count` or `LIMIT row_count OFFSET offset`.

  ‘Example’

 `SELECT * FROM employees LIMIT 5;` — returns the first 5 rows.

  – ‘Example with Offset’  `SELECT * FROM employees LIMIT 5, 10;` — skips the first 5 rows and returns the next 10.

Aliasing in MySQL

-Column Aliasing: Allows renaming of column headings in the result set for better readability or to avoid conflicts.

  – Syntax: `SELECT column_name AS alias_name FROM table_name;`

  -Example’:  `SELECT employee_id AS ID, employee_name AS Name FROM employees;`

  -Table Aliasing:-  Renames a table within a query, especially useful in complex queries or joins.

  -Syntax:- `SELECT t.column_name FROM table_name AS t;`

  – Example:-: `SELECT e.employee_name, d.department_name FROM employees AS e JOIN departments AS d ON e.department_id = d.id;`