What is Data Science? Best Learning Skill in 2021!
You might have come across the term ‘data science’ quite often while studying Computer Programming and Information Technology. But do you know what Data science is? And where is Data Science applied?
Data science has gained a lot of attention in the last decade. Currently Data Science is one of the highly paid fields in computer programming and information technology.
In 2021, learning data science is very beneficial for your career and in this post we will explain why.
Python is programming language that heavily supports Data Science, here is an article discussing the Python language in detail,
In this post we will provide you with a brief explanation on what is data science and related topics.
Also we will provide you an average salary of a data scientist.
So make sure you read this blog post and get full benefits through it.
What is data science?
Before starting with what is data science you should know some basics of data.
What is data?
Data is information in digital format, as encoded text or numbers, or multimedia images, audio, or video.
What is data science?
According to Wikipedia
Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data.
Data science is a field of computer science and information technology that has to deal with managing, processing of big data and operating data.
Data science is defined as the process of obtaining valuable insights and stats from structured and unstructured data by using various tools and techniques; this data is further processed for relevant data visualization.
Programming languages for Data Science:
Python and R are some of the most popular programming languages used in Data Science applications.
R programming language:
R is a famous programming language that was specially developed for statistics and data mining. R has huge applications in Data Science.
Python programming language:
Python is a programming language that is renowned for its AI and data science applications. There are a number of python libraries that are used for data science including pandas, numpy and scipy.
Data science is an interdisciplinary field focused on extracting knowledge from huge data sets. The major levels of Data science include data collection, data analysis, data managing, data processing and data communication.
Data collection :
Data collection involves capturing and identifying data. This data is retrieved from external sources (in the form of text, image, video or audio) and converted into a digital file. This digital data is later identified and sorted according to its data structure.
In various multinational companies, data has to be collected from a huge set of users therefore; Data collection is a very important part of Data Science. This data is stored for further usage.
Data analysis :
Data Analysis is a very important part of data science that involves various essential data processing events. Data Analysis involves inspection, cleaning, transformation and modeling of huge data.
While dealing with large amounts of data, many times fake or irrelevant data is added which may cause problems in a bigger picture, to counter such scenario data inspection and cleaning is done.
After cleaning of data, this data is transformed and modeled into digital format and stored for further application.
Data analysis is a prime field in Data Science, as in this modern world the data is exponentially increasing and processing this data is a very important job.
If there is some error in processing this essential data, such situations may result in heavy losses for a company. Therefore a company needs great data analysts who can handle and avoid this situation.
Data management :
Data management is an administrative process that involves acquiring, validating, storing, securing and processing of collected and analyzed data. Data management ensures data to be more accessible, reliable and readable.
By making use of this huge organized data, important business decision are taken according to customer behavior, trends, opportunities and other deep insights.
Data processing :
Data processing involves conversion of analyzed and managed data to machine readable form, controls flow of data through CPU to output devices, formatting and transformation of huge amounts of data.
Data processing is also a vast field for learning. It is mainly classified into
- Data Mining
- Data clustering and Data classification
- Data modeling
- Data Summarization
Data communication :
Data communication involves transmission and reception of digital data stored in one computer to one or multiple computers.
Data communication allows a computer to exchange information through various sources. The best medium for Data communication is the internet.
This transmission and reception of data can be achieved by using wires, optical fibers or wireless communication systems.
Who is a Data Scientist ?
Data scientist is a person who has mastered the skill of data science. Data scientists use programming languages to perform various operations on extremely large amounts of data.
Data scientists can collect, analyses, process, and interpret required conclusions from the collected data to solve complex problems.
The honorable mentions of some great data scientists in the world
Where is data science applied?
Data Science is a very essential component in this decade as the users on internet and digital platforms are increasing every second. Collecting and processing these huge amounts of data is very important.
Dealing with huge sets of data from the user to generate insights for further improvement and solving complex problems.
Here are some of the basic applications of Data Science,
1. Data Science for Business improvement.
Huge companies use data science to analyze data from their users to improve their marketing strategy and advertisement of products.
A well-established company has users in millions therefore, to analyze customer feedback and to bring better offers and schemes for the users.
2. Data Science for Customer Acquisition.
Data science plays an essential role to acquire and attract customers by analyzing their needs and requirements.
3. Data Science for Enriching lives.
Healthcare and medical industries use data science to analyze and process the available data to provide assistance to customers in daily life.
In healthcare, it is essential to analyze the previous medical history of a patient including personal data to solve problems faced by the patient.
Why to learn Data Science?
Data Science and Data analytics is one of the highest paid roles in computer science and the demand for these roles will keep on increasing in upcoming years.
Use of computer technology and internet has increased drastically in the previous decade and this reliability towards computers is nowhere to be reduced. Instead, usage of computer devices will increase in following years and so will the data of these computers.
Management and analysis of such huge amounts of data will be very essential and so, the demand for data scientists will increase in course time.
How much does a data scientist earn?
Here is a table where you can see the average salary of data scientists in USA and India with different duration of experience.