Are you a professional who is seeking a satisfying high profile and highly paid career? If so, then it’s the field of Big Data Analytics that’s what you should be in, since Big Data continues to grow in stature at Software as a Service (SaaS) companies.Whether you are at the stage of starting or advancing your career in the field of Big Data and data science, here are three important programming languages that you would like to learn to give that career move the much needed impetus: R, Python and Hadoop. Why Should You Learn R?Being a good data scientist requires you to be passionate about coding and statistics; and R, a standard among statistical programming languages, also termed the “golden child” is the best for a statistician to learn. It’s a popular skill sought after by some of the giant brands, including New York Times, Google, Bank of America and Facebook, who seek Big Data analysts and data scientists proficient in R. Further, enterprises appreciate R’s versatility, whose commercial applications are rapidly increasing. Now, if your curiosity been adequately aroused here are a few compelling reasons why you need to add R to your skill-set:-
As opposed to the restrictions imposed by Matlab or SAS, you can freely install, use, modify, update, clone, redistribute and resell R. In other words, R is freely available and is an open-source. Not only does this result in saving money for the enterprise, but it also caters for easy upgrades, which is something very useful for any statistical programming language.R can be run on Windows, Mac OS X, Linux as well as Windows. Being cross-platform compatible, R can also import data from Microsoft Access, Microsoft Excel, SQLite, My SQL, Oracle and other programs.
R is a powerful scripting language which can easily handle large, complex data sets. While R can be used on high performance computer clusters, it is the best language to use for heavy, resource intensive simulations.Having well above 2 million users, R has widespread acclaim.
Being highly flexible and evolved, a horde of new developments in statistics first appear as R packages. Publishers have fallen in love with R because it seamlessly integrates with document preparation systems like LaTeX, implying statistical output and graphics from R can be embedded into word-processing documents.R has a global community of passionate users regularly interacting on discussion forums and who attend conferences. The R community is vibrant, large and a great resource bank. Further, there exist about 2000 free libraries for unlimited use, covering statistical areas of finance, cluster analysis, high performance computing and much more.
Why Should You Learn PythonFirstly, compared to R, Python is easier to learn, despite being a high-level programming language. Secondly, if you wish to make inroads into the fields of Big Data or data science , Python is yet another programming language recommended to be learnt, and is the preferred choice among web and game developers. Here are a few more compelling reasons why Python should be on your learning list for 2018.As brought out earlier,Python is quite easy to learn. The basics of Python are easy to grasp for newcomers, as is the case with C, Java and Perl. Python has user-friendly features like simple syntax, code readability, and ease-of-implementation, therefore a programmer coding in Python writes less code. Detest debugging? Well, the good news is thatPython is easier to debug. Bugs scare almost every programmer, and that is why Python’s unique design is popular among newcomers to data science. Less code to be written implies it is easier to debug. Compared to most of the other languages, programs compiled in Python are less prone to various issues. Python is widely used. Extremely popular, like R, the Python programming language is used in a large variety of software packages and industries. It is Python that powers Google’s search engine, Quora, YouTube, DropBox, Reddit, Disqus and FriendFeed. IBM, NASA and Mozilla have a heavy dependence on Python. One of these giant corporates might be your future employer, in case you are a skilled Python specialist.Python is an object-oriented language. Migration to any other object-oriented language will be easy and seamless, because of your already strong grasp of the fundamentals; you would only be required to learn the syntax of the new language.Python is open source. Startups and smaller companies and smaller teams favor Python because it is simple, free and is an open source programming language. Python is a high-performance language.Python has always been the preferred programming language for building business-critical, yet fast applications.Python works with Rasberry Pi. To be able to realize the full potential ofRaspberry Pi, and do amazing things with it, you must learn Python. Starting from amateurs and going up to expert programmers, anyone can now build real-world applications using Python.Why Should I learn HadoopWish to take a giant leap in the field of Big Data? Well then, Hadoop is the other programming language that you need to know. Should you be debating about which is better to learn: Hadoop or Python, then the following inputs might help. Like R and Python, Hadoop is open-source making it a flexible option. Hadoop is powerful in that it can store and process huge amounts of data with ease. Impressing programmers all over the world with its sheer horsepower and capabilities, Hadoop is versatile, although it is used for warehousingdata, it’s also used for predictive analytics, data discovery and ETL. Forrester has this to say about Hadoop “…it has become a must-have for large enterprises, forming the cornerstone of any flexible future data platforms needed in the age of the customer.” Hadoop has opportunities in a diverse range of roles. Hadoop professionals can secure jobs as Data Scientists, Hadoop Administrators, Hadoop Architects or Hadoop Developers. Hadoop gives rich dividends. Since Hadoop is one of the most sought-after skills in the Big Data market, it is expected that Certified Hadoop developers will be offered lucrative take home paychecks. Hadoop has potential utility and a healthy future. Hadoop will always be an essential skill-set at some point or the other in the career of a Big Data professional. Hadoop usage is increasing at multinational corporations. Most of the giant companies all over the world like Microsoft, Google, eBay, Amazon Web Services, Dell, Yahoo, IBM and Oracle are increasingly relying on Hadoop. It is quite clear that the fields of Big Data and data science will keep growing at a rapid pace in our increasingly data-driven world. You need to ensure that your career keeps up with that rapid growth, with the aid of online courses that would boost your knowledge and credibility.
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