How Is Python Beneficial In Big Data Analysis?

All of us know that big data analytics is the analysis of the data sets that are too big or that are too complex.This is done by the profit making organisations for different purposes.We know that many different types of programming languages like Java, SQL, etc. are available for data science so why to use python for data science. Before going into this we should first understand about python.

Python:

Python is a popular high level programming language which is used by large number of software developers. It was designed in 1991. The syntax of python is very short in length. It also supports a large standard library. Hence python is considered to be one of the best object oriented programming language. The different features of python are:

• Python is very easy to learn and beginners don’t need to worry about the syntax.
• Python is more understandable and readable.
• Python supports many different kinds of platforms such as windows mac, Linux, etc.
• Python uses an interpreter so it checks the code line by line for errors. So it is easy to debug.
• It has a large standard library.
• It can be combined with other programming languages like C, C++ and Java.

Big Data Analytics:

Big data analytics is the analysis of large and complex sets of data. The different benefits of data analysis is that this can be used by different profit making organisations to make smarter business moves and to get over their competition by knowing the recent trends.It is often used to uncover information including hidden patterns, unknown correlations, market trends and customer preferences that can help organizations make informed business decisions.A big data analyst is a person who works on big data analytics.Some skills that are required to be a good data analyst are:

• The programming skills of a big data analyst should be very good and a big data analyst should be full fledged programmer.The important languages that are required to be learned by a big data analyst R, Python, Java, C++, Ruby, SQL,etc.At the minimum one needs to know R, Python, and Java.
• They should have experience with relational and non relational database system.
• They should be good at aptitude skills and statistics.
• The most important requirement of the big data analyst is that they should be an expert on the domain they are working on.

Python and Big Data Analytics:

Here we list out different features how python is very efficient for big data analytics:

• Python is an open source programming language which is available to use on various platforms like windows, Linux, etc.
• Speed is another important factor in the case of python.
• It maintains great transparency between the code and its execution.
• Python is an object oriented programming language which supports many different types of operations like matrix operations, data frames, etc.
• Another important feature of python is that it is made very compatible with hadoop to work with big data.
• It consists of numerous libraries for data science like numpy, panda, etc.
• It is an interpreted programming language so it runs one code at a time.
• It can easily perform data manipulation using numpy and Pandas.

This above image describes the various uses of python in big data analytics.

I hope this article helped you to choose the best object oriented programming language for big data analytics and also helped you to get about the uses pf python.