DS Tutorial Part 1

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What are Data Structures?

A Data Structure (DS) is a way of organizing, managing, and storing data efficiently. It enables efficient access and modification of data, which is crucial for performance optimization in programming.

Why are Data Structures Important?

1. Efficient Data Handling - Organizing data properly leads to better performance.

2. Optimized Searching and Sorting - Helps in efficient algorithms like binary search, quicksort, etc.

3. Memory Management - Reduces unnecessary memory usage.

4. Used in Real-World Applications - From databases to AI, DS plays a key role.

Types of Data Structures

Data structures are categorized into two types:

1. Linear Data Structures

Data is stored in a sequential manner. Examples:

• Array – Fixed-size collection of elements.

• Linked List – Collection of nodes linked together.

• Stack – Follows LIFO (Last In, First Out).

• Queue – Follows FIFO (First In, First Out).

2. Non-Linear Data Structures

Data is stored in a hierarchical or interconnected manner. Examples:

• Trees – Used in databases, file systems, AI.

• Graphs – Used in networking, social media, etc.

• Hash Tables – Used in indexing, caching, and cryptography.

Real-World Applications of Data Structures

✅ Arrays – Used in gaming, caching, and database indexing.
✅ Stacks – Used in undo/redo functionality, backtracking.
✅ Queues – Used in job scheduling, call center handling.
✅ Graphs – Used in Google Maps, social networks.
✅ Trees – Used in file systems, AI decision trees.

Conclusion

Data structures are the foundation of efficient programming. In the next part, we will explore Arrays in depth with code examples.

📢 Stay tuned! Read more at CompilerSutra

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