Data Structures: What It Is, Its Types, & The Key to Solving Somaliland Technology Challenges

Unleash the Power of Data! This article explains Data Structures (Arrays, Linked Lists, and Hash Tables), their Pros & Cons. Discover the 3 Key Solutions to tackle internet challenges, Mobile Money, and Offline Capability specifically in Somaliland.

Introduction

It is the backbone and foundation of software development. It is the way to manage, organize, and store data for easy retrieval and modification. A developer who does not understand how to use the right data structure cannot build complete, functional, efficient, and reliable software, because these developers do not know or understand what a data structure is or what it does.

What is Data Structure?

A data structure is a way of organizing and storing data in a computer to make it easier to work with it. It determines how the data is organized and the operations that can be performed on it. For example, if I want to calculate the average score of students in a class, I need an array to store those scores and display the students' scores.

Why do we need Data Structures in Somaliland?

1. Solving Internet and Speed ​​Problems

2. Managing Mobile Money Methods

3. Building Apps That Work Offline

4. Building Software Developer Talent

Types of Data Structure

1. Primitive

2. Non-Primitive

Primitive

This information is the simplest and most important that a computer can understand directly and is built into various programs. It is a type of computer that is always used because the computer recognizes it immediately.

The most important types include:

Integer (Int): Stores whole numbers (no fractions). (Example: 5, 100, -2).

Float: Stores numbers with a decimal point. (Example: 3.14, 9.99).

Boolean: Stores a binary value (True or False). (Example: True/False).

Character (Char): Stores a single character. (Example: 'A', '7', '@').

Non-Primitive

Are data types that are built from Primitive Data Structures (such as Integer or Character) to store and manage large amounts of related data. They act as a collection of data that is capable of relating that data, thus solving complex problems in Software Development. They are divided into two categories:

1. Linear

They are structures in which data is stored in a sequential manner. This means that each new piece of data follows only the one that came before it or the one that came after it.

Arrays: A collection of data that is ordered.

Linked Lists: Data that is linked, but not contiguous in memory.

Stacks: A LIFO (Last in First Out) system.

2. Non-Linear

They are structures in which data is stored in a non-sequential manner with many branches and sequential connections.

Trees: Data is organized into a root and branches.

Graphs: They are connections between points (nodes) and lines (edges).

Hash Tables: A very fast structure that stores data using "Keys".

Advantage of Data Structure

1. Efficiency: Ensures that the software is fast and can complete the task in a short time, reducing the time it takes to complete the task.

2. Memory Management: Helps us store data in an organized manner, which reduces the amount of computer memory used by software

3. Problem Solving: Has the ability to provide simple ways to organize and tackle large, complex problems, such as network connectivity or managing large amounts of data.

4. Reusability: Built-in structures (such as Linked Lists or Queues) can be reused many times in different programs and applications.

5. Software Scalability: Allows the software to easily handle large amounts of data that will grow in the future without slowing down.

Disadvantage of Data Structure

1. Memory Overhead: Some structures (such as Linked Lists) require additional data to be stored (such as Pointers that point to adjacent data), which consumes more memory than simple Arrays.

2. Time Complexity Cost: Although DS is generally fast, some operations (such as inserting or removing data from large arrays) can take a long time.

3. Complexity: Non-linear structures (such as Trees and Graphs) have complex code that is difficult to write, maintain, or understand.

4. Resource Constraints: An improperly chosen data structure can cause a program to use too many resources unnecessarily.

5. Specific Costs: The main problem with Data Structures is that each one solves one problem well, but causes other problems in unintended ways. For example, Hash Tables provide very fast data access, which is the main advantage of using them.

Data Structures: Solving Somaliland Challenges

Data Structures provide the best way to make software compatible with the challenging conditions of Somaliland. Choosing the right structure is an indispensable key.

1. Slow Internet Speed: We use Hash Tables to access customer data quickly and directly, which makes the App appear fast even on slow networks.

2. Mobile Money Management: The use of Queues is one of the fundamental decisions in the development of financial systems (FinTech), especially those that rely on Mobile Money like Somaliland. Queues ensure that payment transactions, such as sending money or paying bills.

3. Offline Capability: To overcome the problems of intermittent internet, developers use Linked Lists and Arrays to store new user data on the mobile device.

Conclusion

In general, Data Structures are the backbone and foundation of Software Engineering, and are the most important tools used to build any quality software. The main benefits of using the right Data Structures are increased Performance and efficient Memory management, which results in fast and reliable software. However, it should be noted that problems can arise from the wrong choice; Each structure has a specific cost, solving only one problem well, but causing burdens in other areas (such as Hash Tables which are fast in searching, but not good at sorting data). Therefore, the success of the developer lies in the deep understanding of each type, in order to choose the one that best suits the problem he is solving.