18.01.2020

What are algorithms and data structures, and why do I need to focus on them?

Let’s start with an inspirational quote to keep you motivated throughout;

“Every program depends on algorithms and data structures, but few programs depend on the invention of brand new ones.” Kernighan & Pike.


Many beginners in programming search the web, trying to find the answer to the question of how they should study algorithms and data structures. It is one of the initial questions one must ask while entering this study regime but not certainly the first. A more relevant question would be: What are algorithms and data structures, and why do I need to focus on them?

What is an algorithm?

Algorithms are not just a part of IT or people involved in the fields of computer science. They are practically everywhere and involved in each aspect of your life where technology plays its role. They are used in many different fields in medicine, psychology, transportation, and the biggest yet: social media.

Basically, the main essence of an algorithm is anything that can be further broken down into steps. However, they are much more than just instructions. To put it simply, an algorithm is a primary programming tool that teaches you how to define clear steps and solutions to a distinct procedure.

As per the technical definition, an algorithm is a self-contained step-by-step set of operations to be performed. Algorithms perform the calculation, data processing, and/or automated reasoning tasks.

What are the data structures?

Data structures are a defined and orderly set of data, arranged to make a process easier to follow. They store objects and allow their manipulation based on two different types:

  • Linear

    • Arrays

    • Stacks

    • Linked Lists

    • Queues

  • Non-Linear

    • Trees

    • Graphs

    • Tables

    • Sets

How is the algorithm and data structure connected?

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Technology is rapidly advancing, with new innovations taking place every day. Therefore, programming is getting increasingly high in-demand as a skill for any Software Developer. From Smart TVs to ACs, Lights, Traffic Signals, and whatnot, every aspect has some kind of program imbedded to execute the user command line.

It is where data structures and algorithms play the role of identity for a software developer as they are the core reasons behind improving the problem-solving ability of the candidate to a greater extent. It is why many tech-giants focus on measuring the knowledge of the candidate about data structure and algorithms. They want people who think apart from the typical technicalities of designing an algorithm, in turn, saving the company financial and material resources.

Linus Torvalds, the Finnish-American tech-legend and software engineer who is historically the master-mind behind the kernel for LinuxOS, Android and Chrome OS, says:

“I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships.” 

This quote further motivates and emphasizes the importance of data structures for a software developer and that too over coding – something that beginners tend to fall too heavily upon. What many people don’t realize is that major companies that they look after to pursue their dream jobs have a difference of perspective towards data structures and coding. 

Companies like Google, Microsoft and Facebook improve user experience based on considering coding just as an implementation that takes about 20-30% of the time given for a particular project. Mainly their time goes in designing things with optimum algorithms that guarantee results in the best interests of the company by saving its resources like servers, computation powers, monetary assets, etc.

Benefits of learning data structures & algorithms

The advantage of learning data structure and algorithms efficiently may depend on why you actually want to learn them in the first place. The actual reason behind your learning can improve your knowledge in the domain accordingly. For example, some people learn them particularly to suffice job interviews, get academist help, make their resumes look better etc. While others might learn for acing competitive programming, and some might arguably do it for the sake of learning it only.

Regardless of your choice that why you are learning data structures and algorithms, there are benefits pertaining to the knowledge. The following are some of those many benefits.

To write the logical statement

This means that a programmer can script the correct codes if they knew both data structure and algorithm in its collection as well as the individual state. Like how to form and where to use the following statements:

  • If-then-else Statement

The if/then the statement is a conditional programming statement that follows the then keyword and executes its sub-statement, but only if the provided condition evaluates to true. For example:

If x<10 then x := x+1;

In this example, it is understandable that the condition is x<10. The execution statement is the remaining part of the code, where x will increase its value by one if its current value is less than 10. However, the else clause makes it way with a sub-statement. It will be executed instead of the first condition when deemed false. Therefore, the guarantee is that at least one of the two statements is true and will execute.

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  • Loop Statements

As the term ‘loop’ suggests, they are used to perform similarly, if not the same action multiple times consecutively. It makes them an essential part of every programming language there is. There can many different types of loop statements based on the desired outcome. However, there are for core types that are:

  • For

  • While/do

  • Repeat/until

  • Infinite looping

  • Other Statements

Many other statements require a fully developed understanding of data structure and algorithms like:

  • Begin/ End Block Statements – it groups two statements together

  • Flow Control Statements – takes charge of the execution flow

  • Case Statements – splits the code to execute one or neither of the options

  • Locking Statements – protects code so that it runs only once at a time

  • Yield Statements – gathers a sequence to add new value to an already made sequence

To structure the desired data collection process

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Basically, data collection can be any process with a purpose to acquire or provide assistance in the acquisition of data. The collection is achievable by designing, requesting, and obtaining the correct means to acquire the right amount and valuable data pertaining to the query. This means if a developer doesn’t know about the data structure, they won’t set the fields to collect the required data. If anything remained to collect, then the program will not work correctly. The data can either be provided directly by self-enumeration or extracted from official sources depending on the ease of availability.

Data capturing is a process that converts the collected key information into electronic format. The conversion can be automated or involve staff for keying the collected data.

A computer-assisted operation is desirable as large amounts of data collection will induce error and risk accuracy if performed manually. Therefore, data coding is the final step in the 3-part procedure of data structuring, where a process is used to assign a numerical value to a response. This step is what actually requires a complete understanding of data structure in combination with algorithms because if done correctly, it can reduce coding cost, maximize timeliness and enhance data accuracy, all of which are an organization’s goals.

To develop the program process & get desired results

It is one of the major disadvantages for a primary user that only advanced users can make changes to the data structure. Any problem that involves data structure will need expert assistance, and the user cannot merely help themself. This means that if a programmer has an excellent understanding of both data structure and algorithms, then only they may add multiple queries to fetch the exact/appropriate data to show the desired result to the user.

It adds to the importance of learning data structure and algorithm because in order to be efficient in your command line and to secure your skillset, you as a developer need to have the correct understanding of the program procedure and its expected results.

To produce bug-free results

Supposedly you encounter a bug in your code. But before you make any further conclusions, there are several questions you need to answer as the developer:

  • What is the problem?

  • Is the bug or error itself the problem?

  • Is the cause behind the bud/error the actual issue?

How do you go about fixing the problem?

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More than often, a bug is mainly a symptom of an underlying condition. And developers tend to fix the symptom than to reach the actual root cause of it. Several times, you must have noticed that a website opened up but showed warning signs or errors. It is because the connectivity of data with an algorithm was not established. As a result, the system reached an instructed table and tried to fetch the data, but due to unavailability, it generated the error that you saw.

A simple determination test is noticing how many times since the code’s activation have you encountered the bug. If it is the first time, then you are already on the right path to fix the root cause and not just the symptom. However, if it is after a few repetitive errors that now you are considering setting your code, then you would probably need some new ideas to find your programming methodology that fixes the issue once and for all.

For troubleshooting the codes

Sometimes, technology up-gradation and new languages do not support obsolete functions. Programmers receive tasks to edit the system, and if they don’t understand critical data structural and algorithmic conditions, then they won’t be able to troubleshoot and modify the system. One major problem every developer and programmer will agree upon is the more extensive the project, the more there is information to recognize in a short amount of time. Eliminating some of the information somehow would make the process easier. As the root cause of the problem is the inclusion of many files as the contributor of data structure declarations.

Therefore, making changes in an environment where many data structures are interlinked and provide a reference to other similar structures becomes a mess. Hence, recompiling every source file after every change is time-consuming and will generate bugs and errors before the new code is developed in its entirety. According to IBM’s estimate, there were around $3.1 trillion worth of poor quality data cost in US alone. A developer needs in-depth knowledge to suffice such structural changes on a deeper level in a program to save time and costs for the company.

Problems arising while learning

Now that we laid down the foundation of what are data structures and algorithms, how they are connected, what are the benefits of learning them, and much more. There on last detail that may hinder your growth in the said domain. Those are the problems that may arise during your learning program.

Start small

When learning data structures and algorithms, the best way is to start small with simpler topics that allow you to grasp the concepts better. It will not only lay a solid foundation for your learning, but you’ll be able to learn both individual and combined factors of the two-part categories. So of the basic data structures are Arrays, Linked Lists, Stacks and Queues, etc. On the other hand, some basic algorithms are Sorting, Searching, etc.

Lack of Guidance

Data structures and algorithms are mainly an umbrella term for the many different techniques that go into smooth programming. The tough part is there are no specific guidelines about these topics that may pertain to the particular needs of different product-based companies. A beginner can get confused amidst all this hustle and lose track of what already he must have planned before starting this learning.

What order to follow?

Even when a beginner might know that they should start small and only have self-dependency when it comes to learning data structures and algorithms, it can get confusing as to what order to follow. Most beginners won’t even have the slightest idea of what chronological idea they should follow, given their learning sequence.

Bottom Line

With a high emphasis on the topic of data structures and algorithms by tech-giants like Google, Microsoft, Facebook, and Amazon, it has gained recognition worldwide. These tech companies have product-based work, which generates the need for software developers. Hence, even the pay scale of said developers has gone up a lot in recent years.

In conclusion, it can be summarized that data structure and algorithms have always formed a vital part of programming and coding, with an ever-increasing need for knowledge in recent times.

Key Ideas to Take Away

  • An algorithm is a self-contained step-by-step set of operations to be performed. Algorithms perform the calculation, data processing, and/or automated reasoning tasks.

  • Data structures and algorithms play the role of identity for a software developer as they are the core reasons behind improving the problem-solving ability of the candidate to a greater extent.

  • Benefits of learning data structures & algorithms

    • To write the logical statement

    • To structure the desired data collection process

    • To develop the program process & get desired results

    • How do you go about fixing the problem?

    • For troubleshooting the codes

Author Bio:


John William is currently working as a Data Scientist at Crowd Writer, a considerably cheap assignment writing service. You can check the platform to buy assignment for completion of your home assignments. John has both professional and personal interests in data coding and shares them online.




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