Published on Jul 19,2018
1.6K Views
Email Post

For a few years, right from the beginning of the Big Data Era, there are programming languages vying to be the perfect platforms for Big Data solutions. Organizations require large manpower that can be quickly deploy+-ed into Big Data solutions. The search for a simple, easy to use programming language that can be learnt quickly is speeding up.

Python is a preferred high-level, server-side programming language for websites and mobile apps. For both, new and old developers, Python has managed to stay a language of choice with ease. Due to its readability and dense syntax, developers can express a concept with more ease than they can, using other languages. It powers the web apps for Instagram, Pinterest and Rdio through its associated web framework, Django, and is also used by Google, Yahoo and NASA.

Python is ranked fifth according to the RedMonk programming language rankings. It has moved two points up with reference to the rankings released in the year 2013.

Reason #1 : Python + Big Data

One of the biggest benefits of learning Python for big data certification is the added efficiency of using one programming language across different applications. Python can be used across functions, making a data professional adept at handling any data-related query. As a Big Data architect, it is important that you are versatile. The platforms designed should be compatible with multiple platforms like Python, Hadoop, Storm, NoSQL and Map Reduce. Big Data architects cannot work in isolation.

exo

Python is slowly foraying into Big Data in a very significant way. Experts on Dice state that Python for Big Data certification is definitely the combination, which is being sought for. Python and big data feature are among the skills required by Fortune 500 companies. Gaming industry is one such example. A software engineer in the gaming industry is warranted to know a programming language, along with the data screening expertise. Across industries, it is now becoming imperative that a Big Data professional is a programming expert at the same time. There is also an increase in the interest of companies to crunch figures to assess consumer behavior and predict purchase patterns. Not just predictive analytics, but Big Data is slowly foraying into various avenues, be it communication, or performance metrics.

Reason #2 : Job Prospects

As the hiring for Big Data Professional increases, so is the demand for Python Professionals. Organizations are looking for a large talent pool that can understand the simplest of languages, namely Python in order to tackle their Big Data challenges

Currently the job trends are at an all-time high: there is an upward trend noticed in the job postings for the following professionals (Source: www.indeed.com and LinkedIn).

  • NoSQL (54%)
  • Big Data (46%)
  • Hadoop (43%)
  • Python (16%)

The blend of Python with big data is a matter of versatility enabling flexibility to work across platforms. Python’s agility and user experience is charismatic. So Python and big data certainly become an irresistible combination.

Reason #3 : Python vs Others : Coding Difference

Python is easy for analysts to learn and use, but powerful enough to tackle even the most difficult problems in virtually any domain. It integrates well with existing IT infrastructure, and is independent of the platform. With the advent of so many modern languages, Python-based solutions are legendary in terms of performance. The TIOBE index states that Python is one of the most preferred and popular languages in the world, featuring above Perl, Ruby and JavaScript by a wide margin.

Features that make python win over most of the other programming languages available are as follows –

chart

There you have it, 3 Compelling Reasons to learn Python to kickstart your IT career.Get started with your Python Course!

Got a question for us? Mention them in the comments section and we will get back to you.

Related Posts:

Python for Big Data Analytics

Strings in Python

Get started with your Python Course!

About Author
edureka
Published on Jul 19,2018

Share on

Browse Categories

Comments
1 Comment