What is Data Structure?

• Data is a collection of raw facts, figures, or values that can be processed to produce meaningful information.
  • For example:
    • User posts on Instagram
    • Product details on e-commerce platforms
• Structure describes how we store or organize the data.
  • For example:
    • On Instagram, each post is stored with fields like caption, image/video, likes, and comments.
    • On e-commerce platforms, product details are stored with fields like name, price, description and reviews.
• A Data Structure is a way to store and organize data so that operations (Insertion, Deletion, Searching, Updating) can be performed efficiently and quickly
  • For example:
    • Arrays : Stores data in continuous memory using index-based access
    • LinkedList : Stores data in nodes with pointers to the next node, allowing dynamic size and efficient insertions/deletions

• Types of Data Structures:

• Operations on Data Structures:
  • We can perform various operations on data structures to manipulate the data stored within them. Common operations include:
    • Insertion: Adding new data to the structure
    • Deletion: Removing existing data from the structure
    • Traversal: Accessing each element in the structure
    • Updation: Modifying existing data within the structure

What is Algorithm?

• What is an Algorithm?
  • An Algorithm is a step-by-step procedure or set of rules to solve a particular problem.
  • We use algorithms in daily life, for example:
    • ATM Transaction : Steps to withdraw cash, check balance, or transfer money.
    • Cooking Recipe : Steps to prepare a dish, like chopping vegetables, boiling water, and mixing ingredients.
  • In DSA, algorithms are used to solve problems using different approaches such as:
    • Sorting - Arrange data in a specific order
    • Searching - Find specific data in a collection
    • Pathfinding - Find the shortest path in a graph or network
    • Optimization - Improve performance or resource usage
• For a single problem, multiple algorithms may exist. But we need to choose the most efficient one (based on time and space complexity).
  • Choosing the right algorithm helps improve the performance of the program.

• Important Algorithms in DSA:
  • Searching Algorithms: Find the location of an element.
    • Linear Search
    • Binary Search
  • Sorting Algorithms: Rearrange elements in order.
    • Bubble Sort
    • Selection Sort
    • Insertion Sort
    • Merge Sort
    • Heap Sort
    • Quick Sort
  • Graph Traversal / Path-Finding Algorithms:
    • Dijkstra's Algorithm
    • BFS (Breadth-First Search)
    • DFS (Depth-First Search)

• Important Techniques in DSA:
  • Techniques in DSA are general approaches or methods used to design and solve problems efficiently.
  • They are not full algorithms, but strategies that help build or improve algorithms.
  • Some common techniques include:
    • Recursion
    • Backtracking
    • Divide and Conquer
    • Greedy Algorithm
    • Dynamic Programming (DP)

Use of DSA in Real World Applications:

1. Social Media Platforms (e.g., Instagram , Facebook )
   • Use of DSA:
     • Graphs for user connections (friends/followers)
     • Queues for managing news feeds
     • HashMaps for fast user profile lookups
   • Example:
     • Showing your feed based on who you follow and what’s trending.
2. E-commerce Websites (e.g., Amazon, Flipkart)
   • Use of DSA:
     • Arrays and HashMaps to manage inventory
     • Trees and Tries for search autocomplete
     • Sorting and searching algorithms to filter products
   • Example:
     • Displaying products sorted by price, rating, or relevance.
3. Navigation & Maps (e.g., Google Maps)
   • Use of DSA:
     • Graphs for representing routes and intersections
     • Dijkstra’s algorithm for finding the shortest path
   • Example:
     • Finding the fastest route from your location to your destination.

DSA is very popular in product-based companies like Amazon, Flipkart, Google etc. But now-a-days also used in service-based companies like Infosys, TCS, Wipro etc.