Why to Use Python for Big Data Analytics?

When we talk about big data analytics we unknowingly refer to a wide range of tools and techniques that are required and used in order to guide analytics to its desired goal that is to find insights from data. The whole idea of data analytics is established upon a very simple principle – the simple notion of business, knowing what the consumer wants in order to sell more. Well, this is the very commercial side of big data analysis but nothing will be farther from truth if we claim that data analytics has only contributed to the profitability of businesses. Big data analytics has had an important role to play in multiple areas that solely concern the betterment of the public. It has brought more stability to the stock exchange, made digital security way stronger than it previously was, brought revolutionary change in the healthcare domain. We are talking about the general impact of data analytics to describe the role that Python has played and can play in the successful use of data analytics.

A few words for Python

Python big data analytics is one of the most famous modes of analytics operations. Python is a language which is equally capable of general purpose programming and quantitative usage. This language banks upon its simplicity and accessibility. The simple syntax is easy to understand and programming novices find Python very useful and so do experienced professionals. Those who are familiar with C++/C, JAVA, Matlab etc. should find Python very easy to grasp. Python can work wonderfully well in all platforms and holds a wide and vivid pool of possibilities. These are the reasons behind its becoming the most popular programming language.

It has ruled the quantitative field

Python has been used in various quantitative fields such as finance, oil and gases, physics, for decades. It is witness to a considerable number of scientific breakthroughs among those is the discovery of the ‘God Particle’. Anyway, we are more concerned with its possibilities in the field of data analytics. A lot of companies, both new and old are making it a point that their data analyst should be skilled in Python big data analytics. The primary reason behind it is the easy accessibility of this open source language. Among the other reasons are

  • Decent processing speed
  • Workability in all platforms
  • Deals equally well with structured and unstructured data
  • Can handle machine learning algorithms
  • Has large libraries which are vastly capable

Apart from all these, what becomes very crucial is the fact that the updates and developments in Python are quite regular and easily available. The development of new features goes on continuously because this is currently the language that most of the young talents work with. Another reason behind Python’s popularity is that it is easy to learn.

It can handle data processing, analysis, manipulation and visualization. Now, that is an all round performer for you and the best part is – it requires a lesser amount of code than most other languages.

Why and where to train?

Python training is readily available in both online and off line modes in India. The training is rather short in duration but has a considerable amount of depth. This is a language that has been used in both the scientific and the commercial fields for many years and there is a lot more to learn than is possible through the internet. If you want to penetrate the analytics industry with Python training, it suggestible that you go for a full length Python course from any of  the many analytics institutes that are offering a comprehensive course. The course you are choosing can be crucial for your career. It should have the ideal blend of theoretical and practical training and ample scope to evaluate your skills and profitable amount of industry exposure. Learning Python for data analytics can also initiate into the deeper domain of data science and advanced analytics.

Python is a powerful language that you should learn as an analytics enthusiast and aspirant. If you are already operating with equivalent languages like R or SAS, you should still go for Python training because it can open up new opportunities which you do not want to miss

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