What Programming Language is used for Data Analytics

As you have noticed today tutorial topics that what programming language is used for data analytics, is a very interesting topic on which we will discuss in detail. In the end, you will get the answer to this question and you will be able to move to the next step that is to learn that language that is used in data analytics. So let’s start the tutorial step by step.

What is a Programming Language?

The language which is used in developing program is called programming language. The program may be an application, software, project or website, etc. We say it programming language because these are special one language which involves building soft programs. For example, Java, Python, PHP, Ruby, etc are programming languages. Programming languages are categorized into two main types.

• Low-Level Language
• High-Level Language

we did not want to explain both types because we will mix them with today’s topic. So we will learn programming language-related topics in separate tutorials series.

What is Data Analytics?

There are lots of definitions on the internet but according to Wikipedia, I would like to share them with you. And then we will dicuss on that defintion breifley.

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information.

There are different things we have to discuss according to Wikipedia definition.

Inspection: It is the careful examination or scrutiny of data.

Cleaning: You have to clearly analyze the data to extract information

Transforming: It means you need to transfer data into information, on the basis we can make decisions.

Modeling: To making data modeling means, you have to make a conceptual design for better understanding.

Discovering useful information: Now at the end, we need to extract information from structured and unstructured data, that we need.

What is Data Science?

The purpose of data science is to extract useful information from structured or unstructured data. Data science is the interdisciplinary field that uses mathematical or scientific methods, algorithms to extract useful information and insight from data. In other words, it is the field that gives a result in the form of information, using that we can make decisions. If you want to learn data science then you need to strengthen your programming skills, without programming skills you cannot take part in it.

What Programming Language is used for Data Analytics?

What is Python?

Python is the interpreted high-level language that is used for general purposes. Today, the programing languages are used at trends, one of them, Python is also at the top level to others. It is the programming language that is used in different fields as web development, artificial intelligence, data science, data analytics, robotics, computer vision, speech recognition, etc. Due to its high power libraries, it used in different fields to get required functionalities.

Why Python is a Powerful Language?

Python is a powerful language that has the ability to get any kind of functionalities. Mostly in every field, python is used to get programming tasks. Its syntax is very simple and easy to use which does no confuse beginner students. And also some features a python has which make it powerful from one language to another.

• Versatility
• Efficiency
• Reliability
• Speed
• A lot Libraries and Frameworks
• Mature Python Community
• Flexibility
• Automation

Where Python Language is used?

Python is a famous programming language used in different fields for different purposes. Big companies used Python as a programming language in their projects to get the required functionalities. One of them is Google which uses a different variety of programs like system building, code evaluation tools, and system administration tools  APIs.

• Google
• Facebook
• Instagram
• Spotify
• Quora
• Netflix
• Dropbox

Python has different applications which used in different fields to develop powerful software or applications.

• Web Development (e.g Django)
• Artificial Intelligence
• Data Science
• Data Analytics
• Machine Learning
• Robotics
• Computer Vision
• Speech Recognition

Conclusion

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