Python for Big Data

Python and Big Data: Made for Each Other

When considering data, did you ever thought how big is big? Well, we’re living in a world that’s ruled by data. What’s interesting is that it is growing exponentially. In fact, the volume of data is so big and great that the digital universe is estimated to touch 44,000 Exabytes (or 44 trillion gigabytes) by the year 2020, expanding more than nine-fold against 4.4 trillion gigabytes in 2013.

Even more interesting is the thing that data never sleeps and it just keeps getting bigger. The numbers showing the amount of data generation each day are staggering – predicting that, by 2020, for every single person on Earth, there will be created 1.7 MB of data every second, as stated by an article on Forbes. Keeping this astonishing expansion rate of data in mind, everyone can foresee that it is likely to grow even more.

Python has let loose countless opportunities for organizations

With the vast amounts of data available online, it can mean a world of new possibilities and opportunities for research organizations, state authorities, and not to mention, businesses. Speaking of businesses, data can create a lot of value for them, changing the way businesses used to compete and operate.

The effective use of data can help figure out patterns which in turn could be useful in the application of machine learning as well as artificial intelligence. Deriving value from data to uncover, explore, and make smarter, real-time, and fact-based business decisions, however, is only possible when you have the right tools in your arsenal. 

And, PYTHON, without any doubt, is one such great tool. 

Python is being used for a long time to enable easier, faster analysis of Big Data for many reasons. In fact, when it comes to data science and algorithms, it’s hailed as the best and most sought-after language out there, as per various studies (wonder why?).

Python and Big Data

Big data is pretty big and that is the case with Python

Given the gigantic arrays of data to be studied and processed, the language you need is supposed to have the computational power and capacity to not only analyze it but also to make deeper insights available for use.

What gives Python an upper hand is that it has been inbuilt with plethora of libraries – such as, Matplotlib, Pandas, NumPy, and SciPy, to name a few – that can actually be utilized in various ways to take care of problems extremely complex in nature as well as to work with a given data in such a way that quick, meaningful results are generated. On top of that, an increasing number of these libraries are also being developed as the list of users grows in number. 

Python’s Community is diverse and burgeoning

Great software has always great support from great people, and Python, being an open-source programming language, is no exception.

With the vast, growing, and active community support, Python has turned out to be the leading choice for Data Scientists and programmers of today, helping them with expert support to get the better of Python while dealing with Big Data analysis. 

Python & Big Data - A perfect combination

Python is a big of life-saving scientific tools – “free for everyone”

With Python, there comes an extensive list of robust library packages, frameworks, and patches that are truly a life-saver, making the life of Data Scientists much easier. But the best thing about all these powerful Python tools is, they are completely free to use and available for everyone. 

Want to become an expert Data Scientist? You don’t need any subscription, buying of a license, or singing of a contract to begin using Python. It is free for you. Simply bounce onto your computer machine, download the application and you’re good to dive into the fascinating world of data.