SQL in one image

Quick Recap of Essential SQL Concepts

1️⃣ FROM clause: Specifies the tables from which data will be retrieved.
2️⃣ WHERE clause: Filters rows based on specified conditions.
3️⃣ GROUP BY clause: Groups rows that have the same values into summary rows.
4️⃣ HAVING clause: Filters groups based on specified conditions.
5️⃣ SELECT clause: Specifies the columns to be retrieved.
6️⃣ WINDOW functions: Functions that perform calculations across a set of table rows.
7️⃣ AGGREGATE functions: Functions like COUNT, SUM, AVG that perform calculations on a set of values.
8️⃣ UNION / UNION ALL: Combines the result sets of multiple SELECT statements.
9️⃣ ORDER BY clause: Sorts the result set based on specified columns.
🔟 LIMIT / OFFSET (or FETCH / OFFSET in some databases): Controls the number of rows returned and starting point for retrieval.

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🎗 Write a query to find all employees whose salaries exceed the company's average salary.
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🎗 Write a query to find all customers who have placed more than five orders.
🎗 Write a query to count the total number of orders placed by each customer.
🎗 Write a query to list employees who joined the company within the last 6 months.
🎗 Write a query to calculate the total sales amount for each product.
🎗 Write a query to list all products that have never been sold.
🎗 Write a query to remove duplicate rows from a table.
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SQL Commands

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Let's start with the first topic:

SQL Learning Series Part-1

### 1. Introduction to SQL:
SQL (Structured Query Language) is a programming language designed for managing and querying relational databases. It provides a standardized way to interact with databases. The basic structure of an SQL query involves:

SELECT column1, column2 FROM table_name WHERE condition;

- SELECT: Specifies the columns to retrieve.
- FROM: Specifies the table from which to retrieve the data.
- WHERE: Filters the rows based on a condition.

Example:

SELECT first_name, last_name FROM employees WHERE department = 'IT';

This query retrieves the first name and last name of employees working in the IT department.

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SQL Learning Series Part-2

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Querying Data

Now that we understand the basic structure, let's delve into querying data with more detail.

#### SELECT Statement:
The SELECT statement retrieves data from one or more tables. You can select specific columns or use * to select all columns.

-- Selecting specific columns
SELECT column1, column2 FROM table_name;

-- Selecting all columns
SELECT * FROM table_name;

#### Filtering Data with WHERE:
The WHERE clause filters rows based on a specified condition.

SELECT column1, column2 FROM table_name WHERE condition;

Example:

SELECT product_name, price FROM products WHERE category = 'Electronics';

This query retrieves the product names and prices for items in the 'Electronics' category.

#### Sorting Data with ORDER BY:
The ORDER BY clause sorts the result set based on one or more columns.

SELECT column1, column2 FROM table_name ORDER BY column1 [ASC|DESC];

Example:

SELECT product_name, price FROM products ORDER BY price DESC;

This query sorts products by price in descending order.

Understanding these fundamentals is crucial for effective data retrieval.

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SQL Learning Series Part-3

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today, we will learn about Joins in more detail.

Joins allow you to combine rows from two or more tables based on related columns. There are several types of joins:

#### INNER JOIN:
Returns rows when there is a match in both tables.

SELECT column1, column2 FROM table1 INNER JOIN table2 ON table1.column = table2.column;

#### LEFT JOIN (or LEFT OUTER JOIN):
Returns all rows from the left table and matching rows from the right table.

SELECT column1, column2 FROM table1 LEFT JOIN table2 ON table1.column = table2.column;

#### RIGHT JOIN (or RIGHT OUTER JOIN):
Returns all rows from the right table and matching rows from the left table.

SELECT column1, column2 FROM table1 RIGHT JOIN table2 ON table1.column = table2.column;

#### FULL JOIN (or FULL OUTER JOIN):
Returns all rows when there is a match in either table.

SELECT column1, column2 FROM table1 FULL JOIN table2 ON table1.column = table2.column;

Joins are powerful for combining data from different sources.

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SQL LEARNING SERIES PART-4

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today, we will learn about Aggregate Functions

Aggregation functions perform calculations on sets of values and return a single result. Common aggregation functions include:

#### COUNT():
Counts the number of rows in a result set.

SELECT COUNT(column) FROM table;

#### SUM():
Calculates the sum of values in a column.

SELECT SUM(column) FROM table;

#### AVG():
Calculates the average value of a numeric column.

SELECT AVG(column) FROM table;

#### MAX():
Returns the maximum value in a column.

SELECT MAX(column) FROM table;

#### MIN():
Returns the minimum value in a column.

SELECT MIN(column) FROM table;

Example:

SELECT COUNT(order_id), AVG(total_amount) FROM orders WHERE customer_id = 123;

This query counts the number of orders and calculates the average total amount for a specific customer.

Understanding aggregation is crucial for summarizing and analyzing data.

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SQL LEARNING SERIES PART-5

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today, we will learn about Subqueries

Subqueries, also known as nested queries, allow you to use the result of one query within another query. There are different types of subqueries:

#### Subquery in SELECT:
Using a subquery to retrieve a single value.

SELECT column1, (SELECT column2 FROM table2 WHERE condition) AS subquery_result FROM table1;

#### Subquery in WHERE:
Filtering based on the result of a subquery.

SELECT column1 FROM table1 WHERE column2 = (SELECT column3 FROM table2 WHERE condition);

#### Subquery in HAVING:
Filtering aggregated results with a subquery.

SELECT column1, COUNT(column2) FROM table1 GROUP BY column1 HAVING COUNT(column2) > (SELECT threshold FROM settings);

Subqueries are useful for complex queries and can be employed in various parts of a statement.

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SQL LEARNING SERIES PART-6

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today we will learn about Data Modification:

Let's explore how to modify data within a database using SQL. There are three main operations: INSERT, UPDATE, and DELETE.

#### INSERT Statement:
Adds new rows of data into a table.

INSERT INTO table_name (column1, column2) VALUES (value1, value2);

Example:

INSERT INTO employees (first_name, last_name, department) VALUES ('John', 'Doe', 'HR');

#### UPDATE Statement:
Modifies existing data in a table.

UPDATE table_name SET column1 = value1, column2 = value2 WHERE condition;

Example:

UPDATE employees SET department = 'Finance' WHERE last_name = 'Doe';

#### DELETE Statement:
Removes rows from a table based on a condition.

DELETE FROM table_name WHERE condition;

Example:

DELETE FROM employees WHERE last_name = 'Doe';

Ensure caution when performing UPDATE and DELETE operations to avoid unintended consequences.

This is a bit tricky but important concept.

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SQL LEARNING SERIES PART-7

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today we will learn about Data Types and Constraints:

Understanding data types and constraints is crucial for designing a well-structured database.

#### Data Types:
SQL supports various data types, such as INT, VARCHAR, DATE, and more. Each column in a table must be assigned a specific data type.

CREATE TABLE table_name (
    column1 INT,
    column2 VARCHAR(50),
    column3 DATE
);

#### Constraints:
Constraints enforce rules on the data in a table. Common constraints include:

- PRIMARY KEY: Uniquely identifies each record in a table.
- FOREIGN KEY: Establishes a link between two tables.
- NOT NULL: Ensures a column cannot have NULL values.
- UNIQUE: Ensures all values in a column are different.

CREATE TABLE employees (
    employee_id INT PRIMARY KEY,
    first_name VARCHAR(50) NOT NULL,
    last_name VARCHAR(50) NOT NULL,
    department_id INT,
    FOREIGN KEY (department_id) REFERENCES departments(department_id)
);

This creates a table of employees with a primary key, non-null first and last names, and a foreign key linking to the departments table.

Understanding and implementing data types and constraints contribute to a well-designed and efficient database.

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SQL LEARNING SERIES PART-8

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today we will learn about Indexes:

Indexes are crucial for optimizing the performance of database queries by allowing faster retrieval of data. They work similarly to the index of a book, making it quicker to find specific information.

#### Creating Indexes:

CREATE INDEX index_name ON table_name (column1, column2, ...);

Indexes can be created on one or multiple columns.

#### Removing Indexes:

DROP INDEX index_name ON table_name;

Indexes should be used judiciously, as they consume additional storage space and can impact the performance of write operations.

Optimizing queries often involves balancing the use of indexes to speed up read operations without significantly affecting write performance.

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SQL LEARNING SERIES PART-9

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today we will learn about Views:

Views in SQL are virtual tables based on the result of a SELECT query. They provide a way to simplify complex queries and encapsulate logic.

#### Creating a View:

CREATE VIEW view_name AS
SELECT column1, column2 FROM table1 WHERE condition;

#### Querying a View:
Once created, you can treat a view like a regular table in your queries.

SELECT * FROM view_name;

#### Updating a View:
Views can be updated if they are based on simple SELECT statements.

CREATE OR REPLACE VIEW view_name AS
SELECT new_column1, new_column2 FROM new_table WHERE new_condition;

Views are useful for abstracting complex queries and enhancing the security of sensitive data.

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SQL LEARNING SERIES PART-10

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today we will learn about Stored Procedures and Functions:

Stored procedures and functions are precompiled and stored in the database, providing a way to encapsulate and reuse logic on the server side.

#### Stored Procedures:
A stored procedure is a set of SQL statements that can be executed as a single unit.

CREATE PROCEDURE procedure_name
AS
BEGIN
    -- SQL statements
END;

#### Executing a Stored Procedure:

EXEC procedure_name;

#### Functions:
A function returns a value based on input parameters. There are two types: scalar functions and table-valued functions.

CREATE FUNCTION function_name (@param1 INT, @param2 VARCHAR(50))
RETURNS INT
AS
BEGIN
    -- SQL statements
    RETURN some_value;
END;

#### Calling a Function:

SELECT dbo.function_name(param1, param2);

Stored procedures and functions enhance code modularity and maintainability. They are valuable for implementing business logic on the database side.

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