__What is a Data Structure?__

Data structures are just “various ways of storing data on your computer” or “the systematic way of displaying and arranging your data,” according to the simple definition. Any data structure must, most importantly, be effective for any given task. for example, search, data transformation, editing, updating, etc.

__Features of a Data Structure:__

Based on the usage, we may divide a data structure’s three different qualities into three categories.

**Time complexity**

The term “time complexity” refers to the length of time required to complete an activity. To reduce the time complexity as much as feasible, we should pick the appropriate data structure for the situation.

**Correctness based on the particular interface**

Each data structure has an interface that is used in conjunction with the operations that it supports. Similarly to this, the data structure should be correctly implemented and based on the right interface. An ideal implementation of a data structure would have a properly defined interface.

**Space Complexity**

A data structure’s space complexity can be used to calculate how much memory it uses. Finally, for solutions with a lot of data sets, we should optimize our algorithmic approach to reduce space complexity as much as possible.

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**Why do we need any sort of data structure?**

Nowadays, handling a huge number of data records with our standard computers is not a difficult or laborious task thanks to the development of new processors and computer systems. However, when it comes to some unforeseen circumstances depending on factors like data size, retrieval speed, and multi-threaded processing, we should concentrate on developing the appropriate data structure for the scenario.

Consider constructing a basic text search using a large corpus of text that contains millions of records. If you are attempting to process data items in parallel, your execution time shouldn’t be more than a few hundred nanoseconds.You may accomplish those kinds of activities effectively with the aid of a well-designed data structure.

**What is an Algorithm?**

An algorithm is a method that completes any work step-by-step. Alternatively said, an algorithm is a clearly defined set of unambiguous instructions that may be used to complete a task without the use of a specific programming language. In this series, we’ll attempt to construct important data structures and algorithms in the programming languages node.js and python to see how similar they are to one another.

**Properties of a given Algorithm?**

As we previously stated, the algorithm should have a clearly defined set of instructions to complete a particular task, even if you won’t be able to call a collection of instructions to complete a task an algorithm if the following criteria aren’t met.

**Unambiguous**

All of the inputs and outputs, as well as each step of the algorithm, should be transparent

**Finiteness**

After a limited amount of step occurrences, the algorithm should be able to end.

**Feasibility**

The algorithm should be able to use the resources that are available.

**Independent**

The algorithm should contain only language-neutral phases (should be able to implement in any programming language)

**Input**

The algorithm must have zero or more distinct inputs, each of which must be well-defined.

**Output**

The algorithm ought to result in one or more clearly specified outputs (s).

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