Big Data Analytics and Python


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If data is regarded as the new ‘oil’ then big data analytics can be regarded as the ‘refineries’. Today 1.7 megabytes of data is created by every human being on the planet and big data analytics essential in harnessing the power of data.

Big data analytics offers cutting edge tools and platforms which can efficiently store, analyze and visualize massive volumes of data with ease. Python is one such tool with which big data analytics can be effectively performed.

Significance of Python in BDA

In the recent years Python has emerged as the language of choice for big data professionals and data scientists. One of the reasons behind this is the easy learning curve of Python and flexibility. Moreover, the useful libraries provided by Python comes very handy when working in big data:

Easy scientific computation with NumPy and SciPy

NumPy and SciPy are two Python libraries which are used by data professionals to perform complicated scientific calculations easily. Both the libraries are dedicated for specific data science tasks and for their sophisticated algorithms they are immensely popular.

Easy data wrangling or munging with Pandas

Pandas is another key component of Python which enables data analysts to transform and map raw data from one form to another. Pandas is instrumental for performing big data analytics in Python as it enables users to import large data sets quickly.

Effective data visualization with Matplotlib

Data visualization is one of the most essential tasks for big data analysts as without it analytics results can not be communicated and understood properly. The Matplotlib Python package is very popular for data visualization as analysts can easily create vivid pie charts, line graphs and histograms with it.

Easy implementation of ML algorithms with SciKit – Learn

Automation is absolutely imperative in Big Data Analytics without which the entire task becomes time consuming and ineffective. Thus machine learning (ML) models are used for much of the data manipulation and processing tasks. With the Python library called SciKit-learn implementing ML algorithms is very easy as it supports a variety of features like data reduction and clustering.

Besides the useful libraries, Python is also popular because it is open-source and therefore free to use. This is why Python boasts a strong support community where creative and innovative ideas are constantly shared and users support each other.

A career with Python Big Data Analytics in India

India is one of the best places for a career in data analytics at the moment. The country home to more than 500 million internet users and a flourishing digital economy. The analytics industry of the country is full of great opportunity and with big firms like Accenture and Fractal analytics continuously recruiting a certified Python Big Data Analytics professional stands to earn big!