Data Structures: Core Concepts: quick revision, 18 bites

Data Structures Decide Program Speed

Same data, wrong structure, slow code.

A **data structure** is a way of organizing data in memory so operations like search, insert, and delete can be done efficiently.

Takeaway. Picking the right data structure is often more important than writing clever code.

What Exactly Is a Data Structure?

It's not just storage — it's organization.

Takeaway. A data structure = data + the operations allowed on it, defined by how it's organized.

Linear vs Non-Linear Structures

One line or many branches?

Takeaway. Linear structures suit ordered data; non-linear structures model relationships and hierarchies.

Arrays: Fast Access, Costly Resizing

Index in, value out — instantly.

Takeaway. Arrays trade flexibility for speed — great for reads, weak for frequent insertions.

Linked Lists: Flexible but Sequential

No indexes — just pointers.

Takeaway. Linked lists trade fast access for cheap insertions and deletions.

Array vs Linked List

Two ways to store a list.

Takeaway. Choose arrays for lookups, linked lists for frequent insertions/deletions.

Stack: Last In, First Out

Undo works because of stacks.

Takeaway. Stacks model any 'reverse the order' problem — undo, backtracking, function calls.

Queue: First In, First Out

Fairness in data — first come, first served.

Takeaway. Queues model waiting lines — anything that must be processed in arrival order.

Stack vs Queue

LIFO or FIFO — pick your order.

Takeaway. Same operations, opposite order — the use case decides which you need.

Trees: Hierarchical Data

One root, many branches.

Takeaway. Trees model hierarchy and enable fast search when kept balanced.

Graphs: Networks of Anything

Nodes plus edges — relationships mapped.

Takeaway. Graphs are the go-to structure whenever relationships between items matter.

Hash Tables: Near-Instant Lookup

Key in, value out — almost always O(1).

Takeaway. Hash tables give the fastest average lookup — if the hash function is good.

Time Complexity Cheat Sheet

One table, every structure's speed.

Takeaway. Memorize this table — it's the fastest way to pick the right structure in exams and interviews.

Don't Default to Arrays

Arrays aren't always the answer.

Takeaway. The best structure is the one whose slowest operation matches your rarest task.

How to Choose a Data Structure

Four questions, one right answer.

Takeaway. Structure choice follows from your workload — not from habit.

Where You Already Use These

Your apps run on these structures.

Takeaway. Every app you use is quietly built on the right data structures.

Exam Pattern to Remember

Complexity questions love this table.

Takeaway. Most data structure exam questions reduce to one thing: complexity of the right operation.

Remember Stack vs Queue

LIFO vs FIFO — two letters each.

**Stack = LIFO** (Last In, First Out) — like a pile of plates. **Queue = FIFO** (First In, First Out) — like a ticket line.

Takeaway. Plates = Stack, line = Queue. Two images, two structures, never confused again.