Essential Data Structures for Beginners

Data Structures are fundamental concepts in computer science that refer to organizing, managing and storing data so it can be efficiently accessed and modified. Think of it as;

The Library: A Perfect Analogy

Imagine stepping into a library. Upon first look, you might see multiple book rows, but there’s a method to the madness. Libraries use a systematic approach to organize their books, making it easy for visitors to find what they want. This organization mirrors how data structures function in computer science “organization, management and storage”.

And just like the library, Data Structures provide a structured way to handle large amounts of data.

Types of Data Structure 📁

There are two main types of Data Structure;

1. Linear Data Structures 📚: In this, data elements are arranged sequentially, and each element is connected to its next/previous element.

   Imagine a checkout line at a grocery store. Each customer waiting to pay for their groceries represents an element in a linear data structure, arranged sequentially in a specific order. As customers line up, they are connected to the person in front of them and the one behind them, highlighting the sequential nature of this arrangement. When a customer reaches the front of the line, they pay for their items and exit, allowing the next person to step forward. This process mirrors how we navigate elements in a linear data structure, where access is done in a specific sequence. Furthermore, the checkout line operates on a First-In, First-Out (FIFO) principle, meaning the first customer to join the line is the first to be served. Some common examples of linear data structures include Arrays, Linked Lists, Stacks and Queues.

2. Non-Linear Data Structures 🔗: Data elements are arranged in a hierarchical manner and can connect to multiple elements. A relatable real-world example of non-linear data structures can be seen in the organizational chart of a company. In this chart, the CEO is at the top, overseeing various department heads, each of whom may supervise multiple employees. This hierarchical structure allows for a branching connection, where one manager can be linked to several team members and other managers. Examples of non-linear data structures include Trees, Graphs and Hash tables.

Each of the Data Structure above would be explained in-depth in another article.

Why are Data Structures Important❓

• Optimize Performance ⚡️: Using the right data structure can significantly improve the speed of your program. For instance, a binary search tree provides faster lookup times than a simple list.

• Enhance Problem Solving 💡: Knowledge of different data structures helps you tackle problems efficiently. For instance, if you need quick data access, you might use a hash table.

• Improve code readability & maintainability 👨🏾‍🔧: Using the appropriate data structure can make your code cleaner and more intuitive.

• Efficient memory use 💿: Proper use of data structures ensures that memory is used efficiently, helping prevent wastage and ensuring better performance.

• Proper for coding interviews 🧑🏾‍💻: In technical interviews, especially Software Engineering roles, data structure and algorithm questions are quite common. I mean, this series itself was inspired by a Job interview loss I faced a while back due to a lack of DSA knowledge.

A few takes of mine on learning Data Structures; Start simple, solve problems and understand time and space complexity. For each data structure, understand its space and time complexity for different operations (insertion, deletion, sorting, searching). Practice real-world scenarios. And guess what? We will be doing all of this in this series 🥳

In our next chapter, we will be looking at the different data structures and their use case.