Why Learn Data Structure and Algorithms?

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Programming is all about data structures and algorithms. Data structures are used to hold data while algorithms are used to solve the problem using that data.

Let’s start with this motivating quote: “Every program depends on algorithms and data structures, but few programs depend on the invention of brand new ones.” — Kernighan & Pike

Why to Learn Data Structure and Algorithms?
Why to Learn Data Structure and Algorithms?

Data structures and algorithms (DSA) goes through solutions to standard problems in detail and gives you an insight into how efficient it is to use each one of them. It also teaches you the science of evaluating the efficiency of an algorithm. This enables you to choose the best of various choices.

What is an algorithm?

Wikipedia says “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.”

Why to Learn Data Structure and Algorithms ?


As applications are getting complex and data rich, there are three common problems that applications face now-a-days.

  • Data Search
  • Processor speed
  • Multiple requests

To solve the above-mentioned problems, data structures come to rescue. Data can be organized in a data structure in such a way that all items may not be required to be searched, and the required data can be searched almost instantly.

Applications of Data Structure and Algorithms

Algorithm is a step-by-step procedure, which defines a set of instructions to be executed in a certain order to get the desired output.

From the data structure point of view, following are some important categories of algorithms −

Data Structure is a systematic way to organize data in order to use it efficiently. Following terms are the foundation terms of a data structure: Interface, and Implementation.

Characteristics of a Data Structure

  1. Correctness –Any data structure has an interface that defines the processes that the data structure supports. Similarly, the data structure can be applied properly depending on the right interface. A data structure can, in principle, provide a well-defined interface and descriptive implementation.
  2. Time Complexity −The time complexity of a task is known as the running time or execution time. To reduce time complexity as much as possible, we can use the best possible data structure for the given context.
  3. Space Complexity −The memory use of a data structure is determined by space complexity. Finally, for problems containing a huge number of data sets, we can refine our algorithmic approach to eliminate space complexity as much as possible.

Using an appropriate data structure is crucial when working with lots of data. Using the right algorithm plays a significant role in the performance and scalability of your software. Your mobile apps will be more responsive and have better battery life. Your server apps will be able to handle more concurrent requests and use less energy. Algorithms often include proofs of correctness that you can leverage to build better software.

Software Developer interviews at Tech Giants more focused towards Data Structures and Algorithms

If you are going for an interview with some of the Tech Giants like Amazon, Google, Flipkart, etc., or some other high-paying companies for the role of a Software Developer or Backend Developer then you must be good at problem-solving. The interviews in these companies are more focused on analyzing your problem-solving abilities.

Top Companies using Algorithms and Data Structures

  • NASA
  • ISRO
  • Google
  • Amazon
  • Instagram
  • Facebook
  • Reddit
  • Youtube
  • Dropbox
  • Quora
  • Yahoo
  • IBM
  • TCS
  • Infosys

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