We are going to start a series of lessons based on Data Structures and Algorithms.
Objectives of this article:
- Describe what is the importance of a Data Structure
- Describe the term Algorithm
- What are algorithm complexities
- Approaches to solving algorithms
This particular concept is identified as one of the most important concepts in software engineering, and that became a primary checkpoint for most of the top-level companies.
In this lesson series, we will discuss the idea behind data structures and algorithm concepts, and we will implement several algorithms during upcoming lessons.
What is a Data Structure?
The simple definition for the data structure is that “different ways of storing data on your computer” or “the systematic way of representing and organizing your data”.
Importantly, any data structure should be able to use efficiently for any given task. for instance, search, transform data, edit, update, etc.
Features of a Data Structure
There are three different features of a data structure that we can categorize based on the usage.
- Time complexity
Running time or the execution time for a given task is defined as the time complexity. We should use the best possible data structure for the given context to minimize the time complexity as much as possible.
- Correctness based on the particular interface
_Every data structure comprises its __interface _that the operations that support by the given data structure. Similarly, there should be a correct implementation of the data structure based on the correct interface. Ideally, a data structure should come with a correctly defined interface and descriptive implementation.
- Space Complexity
Space complexity will measure the memory usage of a given data structure. Ultimately, we should optimize our algorithmic solution to minimize space complexity as much as possible for solutions with a large number of data sets.
#algorithms #alorithms101 #data analytic
