Written by Sneha Rani on Digilah (Student Tech Research)
My name is Sneha Rani. Currently, I am pursuing B.Tech. in Electronics and Communication from the Indian Institute of Technology (BHU), Varanasi, India. I have keen interest in how large datasets are analyzed and transformed into meaningful results. The key of organisation and retrieval of data lies in data structures and algorithms. Now we are in a world where we have to use our energy to think of better solutions.
Data structures are everywhere!
In the current world where technology is embedded in our daily lives, the importance of data structures and algorithms cannot be doubted. Behind every app, website, and digital service is a large network of data structures and algorithms that are working day and night to make our lives more comfortable, efficient, and fun.
Indeed, the basic ideas of computer science such as the optimization of searching results and the powering of recommendation systems are the ones that are changing the way we interact with technology.
Introduction to DSA
The basic elements of computer science have changed the way we communicate with technology, thus, we could go beyond the possible results of physical labour and concentrate on problem solving which is more creative.
There are numerous data structures and algorithms such as the greedy approach, dynamic programming, graphs, trees, linked lists, arrays and lists, sorting and searching, just to name a few. Whatever you want to do, whether you want to optimize the solution or cut the cost, all can be done by data structures and algorithms in an efficient way.
Dijkstra and Bellman-Ford’s algorithms are designed to help you determine the shortest paths between two nodes while Floyd Warshall’s method is used to calculate the shortest path between each pair of vertices in a graph. Dynamic programming is a process that enables you to save the previous results and compare the new ones to discover the most efficient solution.
Trees can be employed to preserve the integrated structure of the data sets. Arrays give you the possibility to experiment with different dimensions which enables the processing of various kinds of data and operations. Linked lists facilitate you to use the storage efficiently and data can be stored dynamically.
The hashing can cut the search time by an exponential factor, thus, providing a good user experience. Stack and queue are the most beneficial data structures. Stack and queue are as straightforward as taking books from a pile and being in line at the ticket counter. The stack and the queue are used to solve many complex problems at once very easily.
With every dive into the world of data structures we discover its endless possibilities, we are intrigued by its complexities and intricacies, and we are drawn into its depth.
Let us consider some of the applications of data structures and algorithms:
Efficient Information Retrieval
Think of the situation of looking for information on the web without the support of good data structures and algorithms! It would be similar to looking for a needle in a haystack.
Through the use of data structures like hash tables, binary search trees, and algorithms like breadth-first search and depth-first search, search engines can quickly go through the huge amount of data to find the results which are relevant in milliseconds.
You can be looking for a nearby restaurant, researching a topic for a school project, or shopping for a new pair of shoes and data structures and algorithms will ensure that the information you need is in your hands in just a few keystrokes.
Personalized Recommendations
Have you ever realized that the ads on your favourite social media platform always seem to be perfectly tailored to your interests and that your Instagram and Tik-Tok feed feels so familiar? Or how streaming services fight for your viewing time by recommending movies and TV shows that match your viewing habits?
Data structures are the basis of the suggestions given to you by your online shopping app.
The possibility of such a high degree of personalization is due to the use of advanced recommendation algorithms that take into account your past behaviour, preferences, and demographic information to suggest the content that you are likely to enjoy.
Through the use of data structures such as graphs and algorithms like collaborative filtering and content-based filtering, technology firms can generate personalized experiences that make users to stay longer and come back for more.
Optimized Transportation and Navigation
Navigation apps have become vital for travelers who are going to their work, planning a trip, or exploring a new city. Behind the scenes, these apps use data structures like graphs and algorithms like Dijkstra’s shortest path algorithm to calculate the most effective routes, considering factors such as traffic jams, road closures, and real-time updates.
Through the optimization of the transportation routes, data structures and algorithms not only save time and fuel but also cut down on stress and make the whole travel experience a lot more pleasant.
Enhanced Communication and Collaboration
Nowadays, the world is more interconnected than ever, and communication and collaboration are key for both personal and the professional success.
Instant messaging apps, email clients, and collaboration platforms use data structures, such as queues, stacks, and trees, and algorithms, such as sorting and searching, for the fast and efficient delivery of messages.
No matter if you are texting a friend, sending files to coworkers, or attending a virtual meeting, data structures and algorithms make communication and collaboration possible even if the people are in different time zones or across distances.
Let us now delve into some real-life cases where data structures and algorithms are being used:
Artificial Intelligence and Machine Learning
Artificial Intelligence and Machine Learning are the areas in which these intelligent technologies are predominantly being used.
AI and machine learning algorithms usually use special data structures that are designed for data representation and processing, thus making it easier to carry out tasks more quickly and accurately.
For instance, decision trees are employed in classification tasks, while neural networks make use of complex graph-like structures to depict the relations between data points.
Databases
Databases are now everywhere in the present world, they are the engine that drives all from social media to financial systems.
Behind the scenes, databases depend on the complex data structures like B-trees, hash tables, and indexes to store, retrieve, and manage the huge amounts of structured data efficiently.
File Systems
The file systems are the ones that are responsible for the organization and management of the files that are stored on the computers and the storage devices.
Data structures such as linked lists, trees (like B-trees or binary trees), and hash tables are used to keep the file metadata, directory structures, and file locations on the disk.
Financial Systems
Financial systems handle huge amounts of transactional information and perform complex calculations.
Data structures such as priority queues, hash tables, and trees are used to carry out financial instruments, visualize market trends, and improve trading strategies.
Computer Graphics and Gaming
Data structures are the key factor in computer graphics and gaming, which are used to model and manipulate objects, scenes and game states.
For instance, spatial data structures such as octrees are being used for the collision detection and spatial partitioning.
Healthcare Systems
Healthcare systems keep the patient records, medical images, and the treatment plans using data structures like linked lists, trees, and hash tables.
The data structures thus, are the tools that make the organization of patient data, the tracking of the medical histories and the communication between the healthcare providers possible.
Social networks
Social networking platforms are dealing with heaps of user data and connections between users. Graph data structures are used to create social network models, in which nodes are users and edges are the relationships.
Graphs are then utilised to the algorithms which are employed to recommend friends, detect the communities, and analyse the network behaviour.
Competitive Programming
Competitive programming is somewhat like a sport for computer programmers, where the participants are the ones who compete to solve algorithmic and computational problems within a given time frame.
The primary goal of competitive programming is to write efficient and correct code to solve a variety of problems, usually with time limitations.
Competitive programming is a branch that deals with the best use of data structures and algorithms to solve the real world problems using the least resources for the best result.
This calls for a lot of brainstorming. Competitively, data structures are the key to tackling problems in an efficient and effective manner.
They are the tools that enable the users to arrange and manage data in an efficient way. Participants have to not only comprehend the operation of these data structures but also determine when and where to use them to solve various problems.
Conclusion
Through the process of data structures and algorithms, information retrieval is simplified, and personalized experiences are introduced to the real world which is helpful in our daily lives.
Using the basic principles of computer science, the developers and engineers can come up with ingenious solutions that make our life easy, convenient, and more enjoyable.
The ever-changing technology will make the relevance of data structures and algorithms increase even more, thus, leading to the advancements and changing the way we communicate with the world around us.
The central point is that data structures and algorithms are the basic elements of our digital society and thus they are the tools we use to overcome the modern world complexities with confidence and ease.
By adopting data structures and algorithms, we can open new doors, trigger innovation and thus, build the future that the next generations will live in.
References
Data Structures Using C And C++ by Y. Langsam, M. Augenstein And A. M. Tenenbaum
https://www.geeksforgeeks.org/learn-data-structures-and-algorithms-dsa-tutorial
https://www.geeksforgeeks.org/real-time-application-of-data-structures
https://iq.opengenus.org/applications-of-different-data-structures/#google_vignette
Image Sources
https://files.realpython.com/media/How-to-Implement-A-Queue-in-Python_Watermarked.993460fe2ffc.jpg
https://files.realpython.com/media/TOML-in-Python_Watermarked.1bca2ba00140.jpg
Most asked questions
Which data structures are used for non-recursive implementation of programs?
Stack and queue are used to solve many complex problems at once very easily. They are the keys to implement non-recursive solutions of programs.
Which data structures are helpful in visualizing market trends?
Data structures such as priority queues, hash tables, and trees are used to carry out financial instruments, visualize market trends, and improve trading strategies.
Most searched queries
Collaborative filtering
Decision trees
Machine learning
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