🧬 SQL Operators & Conditions – Master Filtering, Matching & Control Logic

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🧲 Introduction – Why Learn SQL Operators & Conditions?

SQL Operators and Conditions allow you to write smarter, more precise queries. Instead of retrieving entire datasets, you can filter, match, compare, and manipulate values with greater flexibility using operators like LIKE, IN, BETWEEN, CASE, and EXISTS.

Whether you’re building dynamic reports or writing complex queries, mastering these conditional techniques gives you fine-grained control over your data.

🎯 In this guide, you’ll learn how to:

• Use SQL conditional logic to match patterns and values
• Apply aliasing and NULL-safe operations
• Write powerful WHERE and SELECT clauses using operators

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📘 Topics Covered

🔖 Concept	📄 Description
🧩 SQL LIKE	Match patterns using wildcards (e.g., names starting with ‘A’)
🎯 SQL IN	Match a value against a list of possible values
🌈 SQL BETWEEN	Filter results within a numeric or date range
🧙 SQL WILDCARDS	Use %, _ and other wildcards to search text
🪞 SQL ALIASES	Rename columns or tables for readability
📌 SQL CASE	Implement IF-THEN-ELSE logic inside queries
🧪 SQL NULL Functions	Handle and evaluate NULL values gracefully
🔣 SQL Operators	Arithmetic, logical, comparison, and bitwise operations
🎛️ SQL ANY, ALL	Compare values to a subquery result set
🧭 SQL EXISTS	Test if subqueries return any results

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🧩 SQL LIKE – Pattern Matching with Wildcards

The LIKE operator is used in a WHERE clause to search for a specified pattern in a column.

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

✅ Finds all names starting with ‘A’.
📎 % matches zero or more characters, _ matches a single character.

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🎯 SQL IN – Check for a Set of Values

IN is used to test whether a value exists in a list of values.

SELECT * FROM employees
WHERE department IN ('HR', 'Sales', 'IT');

✅ Matches multiple values with clean syntax.
📌 Equivalent to multiple OR conditions.

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🌈 SQL BETWEEN – Range Filtering

BETWEEN filters results within a specified range, inclusive of boundary values.

SELECT * FROM orders
WHERE order_date BETWEEN '2024-01-01' AND '2024-12-31';

✅ Used with numbers, dates, or text.
📎 Includes both ends of the range.

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🧙 SQL WILDCARDS – Advanced Pattern Search

Wildcards extend the power of the LIKE operator:

Symbol	Meaning
%	Any sequence of characters
_	Single character
[a-z]	Any character in range
[^a-z]	Any character not in range

SELECT * FROM files
WHERE filename LIKE 'data_%.csv';

📌 Finds CSV files starting with data_.

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🪞 SQL ALIASES – Rename Columns or Tables

Aliases make your output more readable and simplify complex queries.

SELECT first_name AS name
FROM customers;

✅ You can also alias tables in joins:

SELECT e.name FROM employees AS e;

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📌 SQL CASE – Conditional Logic Inside Queries

CASE acts like IF-ELSE for SQL.

SELECT name, 
  CASE 
    WHEN score >= 90 THEN 'A'
    WHEN score >= 75 THEN 'B'
    ELSE 'C'
  END AS grade
FROM students;

📌 Enables dynamic labels and categories based on column values.

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🧪 SQL NULL Functions – Handle Missing Data

Functions that work with NULLs:

• IS NULL / IS NOT NULL
• COALESCE() – Returns first non-NULL value
• IFNULL() – Replaces NULL with a default

SELECT name, COALESCE(phone, 'Not Available') AS contact
FROM users;

📎 Ensures better data presentation and logic.

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🔣 SQL Operators – Arithmetic, Logical & Comparison

Category	Operators
Arithmetic	+, -, *, /, %
Comparison	=, !=, <>, <, >, <=, >=
Logical	AND, OR, NOT

SELECT * FROM products
WHERE price > 100 AND stock != 0;

✅ Combine multiple conditions seamlessly.

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🎛️ SQL ANY, ALL – Compare Against Subqueries

• ANY – True if any value matches
• ALL – True only if all values match

SELECT name FROM employees
WHERE salary > ALL (SELECT salary FROM interns);

📎 Checks if an employee earns more than all interns.

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🧭 SQL EXISTS – Check for Subquery Result

EXISTS returns TRUE if the subquery returns any result.

SELECT name FROM departments d
WHERE EXISTS (
  SELECT 1 FROM employees e
  WHERE e.department_id = d.id
);

✅ Often used to test presence or relationships.

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📘 Best Practices for Using SQL Conditions

✅ Do This	❌ Avoid This
Use IN, LIKE, BETWEEN for clean filters	Avoid long OR chains
Use CASE for categorization	Avoid nested IF logic
Alias tables/columns for clarity	Don’t rely on column positions
Always test NULL with IS NULL	Never use = NULL

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📌 Summary – Recap & Next Steps

SQL Operators and Conditions let you filter, manipulate, and structure data with precision. These tools form the backbone of writing clear, efficient, and dynamic SQL queries.

🔍 Key Takeaways:

• Use pattern-based matching with LIKE, WILDCARDS, BETWEEN, and IN
• Implement logic flows using CASE, EXISTS, and NULL functions
• Alias your data for clarity and readability

⚙️ Real-World Relevance:
Used in reporting, dynamic dashboards, filtering user input, and building responsive database-driven apps.

➡️ Next Up: Learn about SQL Joins to combine data from multiple tables.

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❓ FAQs – SQL Operators & Conditions

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❓ What is the difference between IN and EXISTS?
✅ IN compares a column to a list; EXISTS checks for the presence of any record from a subquery.

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❓ How does BETWEEN work with dates?
✅ BETWEEN includes the start and end dates in the filter.

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❓ Can I use aliases in WHERE clause?
✅ No. Aliases defined in SELECT can’t be used directly in WHERE.

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❓ What is the purpose of the CASE statement?
✅ CASE is used for conditional logic—like applying categories or labels based on a value.

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❓ What’s the best way to handle NULL values?
✅ Use COALESCE() or IFNULL() to replace them, and use IS NULL for filtering.

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