Data is the heartbeat of the digital realm. And when something is so important, you want to ensure you deal with it properly. That’s where data structures come into play.

But what is data structure exactly?

In the simplest terms, a data structure is a way of organizing data on a computing machine so that you can access and update it as quickly and efficiently as possible. For those looking for a more detailed data structure definition, we must add processing, retrieving, and storing data to the purposes of this specialized format.

With this in mind, the importance of data structures becomes quite clear. Neither humans nor machines could access or use digital data without these structures.

But using data structures isn’t enough on its own. You must also use the right data structure for your needs.

This article will guide you through the most common types of data structures, explain the relationship between data structures and algorithms, and showcase some real-world applications of these structures.

Armed with this invaluable knowledge, choosing the right data structure will be a breeze.

Types of Data Structures

Like data, data structures have specific characteristics, features, and applications. These are the factors that primarily dictate which data structure should be used in which scenario. Below are the most common types of data structures and their applications.

Primitive Data Structures

Take one look at the name of this data type, and its structure won’t surprise you. Primitive data structures are to data what cells are to a human body – building blocks. As such, they hold a single value and are typically built into programming languages. Whether you check data structures in C or data structures in Java, these are the types of data structures you’ll find.

  • Integer (signed or unsigned) – Representing whole numbers
  • Float (floating-point numbers) – Representing real numbers with decimal precision
  • Character – Representing integer values as symbols
  • Boolean – Storing true or false logical values

Non-Primitive Data Structures

Combine primitive data structures, and you get non-primitive data structures. These structures can be further divided into two types.

Linear Data Structures

As the name implies, a linear data structure arranges the data elements linearly (sequentially). In this structure, each element is attached to its predecessor and successor.

The most commonly used linear data structures (and their real-life applications) include the following:

  • In arrays, multiple elements of the same type are stored together in the same location. As a result, they can all be processed relatively quickly. (library management systems, ticket booking systems, mobile phone contacts, etc.)
  • Linked lists. With linked lists, elements aren’t stored at adjacent memory locations. Instead, the elements are linked with pointers indicating the next element in the sequence. (music playlists, social media feeds, etc.)
  • These data structures follow the Last-In-First-Out (LIFO) sequencing order. As a result, you can only enter or retrieve data from one stack end (browsing history, undo operations in word processors, etc.)
  • Queues follow the First-In-First-Out (FIFO) sequencing order (website traffic, printer task scheduling, video queues, etc.)

Non-Linear Data Structures

A non-linear data structure also has a pretty self-explanatory name. The elements aren’t placed linearly. This also means you can’t traverse all of them in a single run.

  • Trees are tree-like (no surprise there!) hierarchical data structures. These structures consist of nodes, each filled with specific data (routers in computer networks, database indexing, etc.)
  • Combine vertices (or nodes) and edges, and you get a graph. These data structures are used to solve the most challenging programming problems (modeling, computation flow, etc.)

Advanced Data Structures

Venture beyond primitive data structures (building blocks for data structures) and basic non-primitive data structures (building blocks for more sophisticated applications), and you’ll reach advanced data structures.

  • Hash tables. These advanced data structures use hash functions to store data associatively (through key-value pairs). Using the associated values, you can quickly access the desired data (dictionaries, browser searching, etc.)
  • Heaps are specialized tree-like data structures that satisfy the heap property (every tree element is larger than its descendant.)
  • Tries store strings that can be organized in a visual graph and retrieved when necessary (auto-complete function, spell checkers, etc.)

Algorithms for Data Structures

There is a common misconception that data structures and algorithms in Java and other programming languages are one and the same. In reality, algorithms are steps used to structure data and solve other problems. Check out our overview of some basic algorithms for data structures.

Searching Algorithms

Searching algorithms are used to locate specific elements within data structures. Whether you’re searching for specific data structures in C++ or another programming language, you can use two types of algorithms:

  • Linear search: starts from one end and checks each sequential element until the desired element is located
  • Binary search: looks for the desired element in the middle of a sorted list of items (If the elements aren’t sorted, you must do that before a binary search.)

Sorting Algorithms

Whenever you need to arrange elements in a specific order, you’ll need sorting algorithms.

  • Bubble sort: Compares two adjacent elements and swaps them if they’re in the wrong order
  • Selection sort: Sorts lists by identifying the smallest element and placing it at the beginning of the unsorted list
  • Insertion sort: Inserts the unsorted element in the correct position straight away
  • Merge sort: Divides unsorted lists into smaller sections and orders each separately (the so-called divide-and-conquer principle)
  • Quick sort: Also relies on the divide-and-conquer principle but employs a pivot element to partition the list (elements smaller than the pivot element go back, while larger ones are kept on the right)

Tree Traversal Algorithms

To traverse a tree means to visit its every node. Since trees aren’t linear data structures, there’s more than one way to traverse them.

  • Pre-order traversal: Visits the root node first (the topmost node in a tree), followed by the left and finally the right subtree
  • In-order traversal: Starts with the left subtree, moves to the root node, and ends with the right subtree
  • Post-order traversal: Visits the nodes in the following order: left subtree, right subtree, the root node

Graph Traversal Algorithms

Graph traversal algorithms traverse all the vertices (or nodes) and edges in a graph. You can choose between two:

  • Depth-first search – Focuses on visiting all the vertices or nodes of a graph data structure located one above the other
  • Breadth-first search – Traverses the adjacent nodes of a graph before moving outwards

Applications of Data Structures

Data structures are critical for managing data. So, no wonder their extensive list of applications keeps growing virtually every day. Check out some of the most popular applications data structures have nowadays.

Data Organization and Storage

With this application, data structures return to their roots: they’re used to arrange and store data most efficiently.

Database Management Systems

Database management systems are software programs used to define, store, manipulate, and protect data in a single location. These systems have several components, each relying on data structures to handle records to some extent.

Let’s take a library management system as an example. Data structures are used every step of the way, from indexing books (based on the author’s name, the book’s title, genre, etc.) to storing e-books.

File Systems

File systems use specific data structures to represent information, allocate it to the memory, and manage it afterward.

Data Retrieval and Processing

With data structures, data isn’t stored and then forgotten. It can also be retrieved and processed as necessary.

Search Engines

Search engines (Google, Bing, Yahoo, etc.) are arguably the most widely used applications of data structures. Thanks to structures like tries and hash tables, search engines can successfully index web pages and retrieve the information internet users seek.

Data Compression

Data compression aims to accurately represent data using the smallest storage amount possible. But without data structures, there wouldn’t be data compression algorithms.

Data Encryption

Data encryption is crucial for preserving data confidentiality. And do you know what’s crucial for supporting cryptography algorithms? That’s right, data structures. Once the data is encrypted, data structures like hash tables also aid with value key storage.

Problem Solving and Optimization

At their core, data structures are designed for optimizing data and solving specific problems (both simple and complex). Throw their composition into the mix, and you’ll understand why these structures have been embraced by fields that heavily rely on mathematics and algorithms for problem-solving.

Artificial Intelligence

Artificial intelligence (AI) is all about data. For machines to be able to use this data, it must be properly stored and organized. Enter data structures.

Arrays, linked lists, queues, graphs, and stacks are just some structures used to store data for AI purposes.

Machine Learning

Data structures used for machine learning (MI) are pretty similar to other computer science fields, including AI. In machine learning, data structures (both linear and non-linear) are used to solve complex mathematical problems, manipulate data, and implement ML models.

Network Routing

Network routing refers to establishing paths through one or more internet networks. Various routing algorithms are used for this purpose and most heavily rely on data structures to find the best patch for the incoming data packet.

Data Structures: The Backbone of Efficiency

Data structures are critical in our data-driven world. They allow straightforward data representation, access, and manipulation, even in giant databases. For this reason, learning about data structures and algorithms further can open up a world of possibilities for a career in data science and related fields.

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OPIT Supporting a New Generation of Cybersecurity Leaders
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Aug 28, 2025 5 min read

The Open Institute of Technology (OPIT) began enrolling students in 2023 to help bridge the skills gap between traditional university education and the requirements of the modern workplace. OPIT’s MSc courses aim to help professionals make a greater impact on their workplace through technology.

OPIT’s courses have become popular with business leaders hoping to develop a strong technical foundation to understand technologies, such as artificial intelligence (AI) and cybersecurity, that are shaping their industry. But OPIT is also attracting professionals with strong technical expertise looking to engage more deeply with the strategic side of digital innovation. This is the story of one such student, Obiora Awogu.

Meet Obiora

Obiora Awogu is a cybersecurity expert from Nigeria with a wealth of credentials and experience from working in the industry for a decade. Working in a lead data security role, he was considering “what’s next” for his career. He was contemplating earning an MSc to add to his list of qualifications he did not yet have, but which could open important doors. He discussed the idea with his mentor, who recommended OPIT, where he himself was already enrolled in an MSc program.

Obiora started looking at the program as a box-checking exercise, but quickly realized that it had so much more to offer. As well as being a fully EU-accredited course that could provide new opportunities with companies around the world, he recognized that the course was designed for people like him, who were ready to go from building to leading.

OPIT’s MSc in Cybersecurity

OPIT’s MSc in Cybersecurity launched in 2024 as a fully online and flexible program ideal for busy professionals like Obiora who want to study without taking a career break.

The course integrates technical and leadership expertise, equipping students to not only implement cybersecurity solutions but also lead cybersecurity initiatives. The curriculum combines technical training with real-world applications, emphasizing hands-on experience and soft skills development alongside hard technical know-how.

The course is led by Tom Vazdar, the Area Chair for Cybersecurity at OPIT, as well as the Chief Security Officer at Erste Bank Croatia and an Advisory Board Member for EC3 European Cybercrime Center. He is representative of the type of faculty OPIT recruits, who are both great teachers and active industry professionals dealing with current challenges daily.

Experts such as Matthew Jelavic, the CEO at CIM Chartered Manager Canada and President of Strategy One Consulting; Mahynour Ahmed, Senior Cloud Security Engineer at Grant Thornton LLP; and Sylvester Kaczmarek, former Chief Scientific Officer at We Space Technologies, join him.

Course content includes:

  • Cybersecurity fundamentals and governance
  • Network security and intrusion detection
  • Legal aspects and compliance
  • Cryptography and secure communications
  • Data analytics and risk management
  • Generative AI cybersecurity
  • Business resilience and response strategies
  • Behavioral cybersecurity
  • Cloud and IoT security
  • Secure software development
  • Critical thinking and problem-solving
  • Leadership and communication in cybersecurity
  • AI-driven forensic analysis in cybersecurity

As with all OPIT’s MSc courses, it wraps up with a capstone project and dissertation, which sees students apply their skills in the real world, either with their existing company or through apprenticeship programs. This not only gives students hands-on experience, but also helps them demonstrate their added value when seeking new opportunities.

Obiora’s Experience

Speaking of his experience with OPIT, Obiora said that it went above and beyond what he expected. He was not surprised by the technical content, in which he was already well-versed, but rather the change in perspective that the course gave him. It helped him move from seeing himself as someone who implements cybersecurity solutions to someone who could shape strategy at the highest levels of an organization.

OPIT’s MSc has given Obiora the skills to speak to boards, connect risk with business priorities, and build organizations that don’t just defend against cyber risks but adapt to a changing digital world. He commented that studying at OPIT did not give him answers; instead, it gave him better questions and the tools to lead. Of course, it also ticks the MSc box, and while that might not be the main reason for studying at OPIT, it is certainly a clear benefit.

Obiora has now moved into a leading Chief Information Security Officer Role at MoMo, Payment Service Bank for MTN. There, he is building cyber-resilient financial systems, contributing to public-private partnerships, and mentoring the next generation of cybersecurity experts.

Leading Cybersecurity in Africa

As well as having a significant impact within his own organization, studying at OPIT has helped Obiora develop the skills and confidence needed to become a leader in the cybersecurity industry across Africa.

In March 2025, Obiora was featured on the cover of CIO Africa Magazine and was then a panelist on the “Future of Cybersecurity Careers in the Age of Generative AI” for Comercio Ltd. The Lagos Chamber of Commerce and Industry also invited him to speak on Cybersecurity in Africa.

Obiora recently presented the keynote speech at the Hackers Secret Conference 2025 on “Code in the Shadows: Harnessing the Human-AI Partnership in Cybersecurity.” In the talk, he explored how AI is revolutionizing incident response, enhancing its speed, precision, and proactivity, and improving on human-AI collaboration.

An OPIT Success Story

Talking about Obiora’s success, the OPIT Area Chair for Cybersecurity said:

“Obiora is a perfect example of what this program was designed for – experienced professionals ready to scale their impact beyond operations. It’s been inspiring to watch him transform technical excellence into strategic leadership. Africa’s cybersecurity landscape is stronger with people like him at the helm. Bravo, Obiora!”

Learn more about OPIT’s MSc in Cybersecurity and how it can support the next steps of your career.

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How Regenerative Business Models Are Redefining Innovation and Sustainability
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Aug 18, 2025 6 min read

Open Institute of Technology (OPIT) masterclasses bring students face-to-face with real-world business challenges. In OPIT’s July masterclass, OPIT Professor Francesco Derchi and Ph.D. candidate Robert Mario de Stefano explained the principles of regenerative businesses and how regeneration goes hand in hand with growth.

Regenerative Business Models

Professor Derchi began by explaining what exactly is meant by regenerative business models, clearly differentiating them from sustainable or circular models.

Many companies pursue sustainable business models in which they offset their negative impact by investing elsewhere. For example, businesses that are big carbon consumers will support nature regeneration projects. Circular business models are similar but are more focused on their own product chain, aiming to minimize waste by keeping products in use as long as possible through recycling. Both models essentially aim to have a “net-zero” negative impact on the environment.

Regenerative models are different because they actively aim to have a “net-positive” impact on the environment, not just offsetting their own use but actively regenerating the planet.

Massive Transformative Purpose

While regenerative business models are often associated with philanthropic endeavors, Professor Derchi explained that they do not have to be, and that investment in regeneration can be a driver of growth.

He discussed the importance of corporate purpose in the modern business space. Having a strong and clearly stated corporate purpose is considered essential to drive business decision-making, encourage employee buy-in, and promote customer loyalty.

But today, simple corporate missions, such as “make good shoes,” don’t go far enough. People are looking for a Massive Transformational Purpose (MTP) that can take the business to the next level.

Take, for example, Ben & Jerry’s. The business’s initial corporate purpose may have been to make great ice cream and serve it up in a way that people will enjoy. But the business really began to grow when they embraced an MTP. As they announced in their mission statement, “We believe that ice cream can change the world.” Their business activities also have the aim of advancing human rights and dignity, supporting social and economic justice, and protecting and restoring the Earth’s natural systems. While these aims are philanthropic, they have also helped the business grow.

RePlanet

Professor Derchi next talked about RePlanet, a business he recently worked to develop their MTP. Founded in 2015, RePlanet designs and implements customized renewable energy solutions for businesses and projects. The company already operates in the renewable energy field and ranked as the 21st fastest-growing business in Italy in 2023. So while they were already enjoying great success, Derchi worked with them to see if actively embracing a regenerative business model could unlock additional growth.

Working together, RePlanet moved towards an MTP of building a greener future based on today’s choices, ensuring a cleaner world for generations. Meeting this goal started with the energy products that RePlanet sells, such as energy systems that recover heat from dairy farms. But as the business’s MTP, it goes beyond that. RePlanet doesn’t just engage suppliers; it chooses partners that share its specific values. It also influences the projects they choose to work on – they prioritize high-impact social projects, such as recently installing photovoltaic energy systems at a local hospital in Nigeria – and how RePlanet treats its talent, acknowledging that people are the true energy of the company.

Regenerative Business Strategies

Based on work with RePlanet and other businesses, Derchi has identified six archetypal regenerative business strategies for businesses that want to have both a regenerative impact and drive growth:

  • Regenerative Leadership – Laying the foundation for regeneration in a broader sense throughout the company
  • Nature Regeneration – Strategies to improve the health of the natural world
  • Social Regeneration – Regenerating human ecosystems through things such as fair-trade practices
  • Responsible Sourcing – Empowering and strengthening suppliers and their communities
  • Health & Well-being – Creating products and services that have a positive effect on customers
  • Employee Focus – Improve work conditions, lives, and well-being of employees.

Case Studies

Building on the concept of regenerative business models, Roberto Mario de Stefano shared other case studies of businesses that are having a positive impact and enjoying growth thanks to regenerative business models and strategies.

Biorfarm

Biorfarm is a digital platform that supports small-scale agriculture by creating a direct link between small farmers and consumers. Cutting out the middleman in modern supply chains means that farmers earn about 50% more for their produce. They set consumers up as “digital farmers” who actively support and learn about farming activities to promote more conscious food consumption.

Their vision is to create a food economy in which those who produce food and those who consume it are connected. This moves consumers from passive cash cows for large corporations that prioritize profits over the well-being of farmers to actively supporting natural production and a more sustainable system.

Rifo Lab

Rifo Lab is a circular clothing brand with the vision of addressing the problem of overproduction in the clothing industry. Established in Prato, Italy, a traditional textile-producing area, the company produces clothes made from textile waste and biodegradable materials. There are no physical stores, and all orders must be placed online; everything is made to order, reducing excess production.

With an eye on social regeneration, all production takes place within 30 kilometers of their offices, allowing the business to support ethical and local production. They also work with companies that actively integrate migrants into the local community, sharing their local artisan crafts with future generations.

Ogyre

Ogyre is a digital platform that allows you to pay fishermen to fish for waste. When fishermen are out conducting their livelihood, they also collect a significant amount of waste from the ocean, especially plastic waste. Ogyre arranges for fishermen to get paid for collecting that waste, which in turn supports the local fishing communities, and then transforms the waste collected into new sustainable products.

Moving Towards a Regenerative Future

The masterclass concluded with a Q&A session, where it explained that working in regenerative businesses requires the same skills as any other business. But it also requires you to embrace a mindset where value comes from giving and that growth is about working together for a better future, and not just competition.

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