Reasons You Should Learn R, Python, and Hadoop

              The world of software technology is a fast evolving one. New technologies are always emerging in the scene. If you want to make your mark in the field then you need to keep the pace with the latest developments in the field. The competency of software professional is measured by his/her knowledge of the most advanced technology. Now, today, we are talking about two of the technologies that everyone is talking about of late-Python and Hadoop

What is Python?

Well, as you might know, Python is a programming language used for general purpose coding. Python is a design language that focuses extensively on code readability. One of the most noticeable features of Python is the use of whitespace indentation to delimit code blocks rather than using curly braces or keywords. Another great advantage of Python over similar languages such as Java and C++ is that is allows expressing concepts in fewer lines. Because of these advantages, Python is one of the most widely used design languages in the world today.

The Core Philosophy of Python :

The core philosophy of python is summarized in the Zen of Python. It is based on certain aphorisms like

• Beautiful is Better than Ugly
• Readability Counts
• Simple is better than Complex
• Complex is better than Complicated
• Explicit is Better Than Implicit

Where is Python Used?

Python is everywhere. This statement perfectly summarizes the wide range of areas that Python is used today. Python is extensively used in the following fields

• Desktop Based GUI Applications

Python can be used to design a variety of Desktop Based GUI Applications with the help of toolkits like PyGtk, PyQt and wxPython. Some of the specific areas which Python has worked its magic include

• Scientific and Computational Applications

There are certain tools that are specifically designed to develop Scientific and Computational Tools using Python. Examples include Numeric Python and Scientific Python. FreeCAD, 3D Modeling Software and Abaqus, finite element method software has been developed using Python

• Image Processing and Graphic Design Applications

Python has been used to design 2D Imaging Software like ImageScape, GIMP and Scribus. It is also used, in varying degrees, to design 3D animation packages like Maya, 3ds Max, Houdini, Blender, Lightwave, Cinema 4D and Houdini

• Games

Python is also used to develop games such as Civilization IV, Vega Strike and the likes. There are a number of 3D Game Engines like PySoy which is used to develop games.

• Web Frameworks

A number of Web Frameworks like Django, TurboGears and CherryPy and certain others as well.

The Advantages of Python :

So, what are the advantages of Python? Well, since a lot of people are talking about it, there’s has to be some benefits right? There are benefits and a lot of it! Let’s take a look at some of them

• Easy to Learn

For a programmer, one of the biggest advantages of Python is that it is easy to learn. You just need to follow the programming guidelines, set forward in the PEP 8, and you are good to go.

• Productivity and Speed

If you are a programmer, especially a freelance programmer, then time is literally money for you. Programming with Python takes less time. This means that you would be able to execute more projects in less time.

• Wide Range of Applications

Python is used in a variety of fields. For example, it is used in Google App Engine, YouTube, Facebook and a ton of other places. Therefore, being an expert in Python can land you a job at these places. That’s quite motivating, wouldn’t you say?

Okay, now that we have learned something about Python and how it would help you, let’s move on to another technology whose knowledge would make you to be considered as a competent professional. Let us now know a bit something about Hadoop.

What is Hadoop?

Hadoop, or more precisely Apache Hadoop, is an open source software framework which is used for Data Storage and for processing very large sets of data.  At the Core of Hadoop, you have two essential parts – The Storage Part, which is known as Hadoop File Distribution System (HDFS) and the processing part.

The base Hadoop Framework consists of the following modules

• Hadoop Distributed File System (HDFS) – A distributed file system that stores data on the commodity machines.
• Hadoop MapReduce- This is an implementation of MapReduce programming for large scale data processing
• Hadoop Common – The Hadoop Common contains the libraries and the utilities that can be used by other modules
• Hadoop YARN – The resource management platform.

The Future of Python and Hadoop :

The future looks bright for both Python and Hadoop. Since, Python has a number of advantages, the demand is huge for people who have a great deal of knowledge about Python.

Big Data is another frontier that is going to see a lot of growth. Since, Hadoop is one of the widely used frameworks for Big Data Processing, knowing Hadoop would surely be an added advantage.

Types of Job You Can Get :

Knowing Python would increase your chances of getting a job as programmer, and decent ones at that. A lot of companies are using Python for designing a wide range of software applications.

Knowing both Hadoop and Python would also increase your chances of getting a job in Big Data Analysis. Hadoop would help you to process the large data sets and Python would help you in the actual process of analysis.

If you are software professional who wants a better paying job in the industry, then having in expertise in the most modern technology would only increase your chances of getting your dream job. Hadoop and Python are two of the technologies that have been in huge demand in recent times and the future shows no signs of change in their popularity. So, learn new stuff as that would always open up new windows of opportunity.

Benefits of learning major three programming languages used: R, Python, and Hadoop.

Why go for R programming?

A good data scientist is the one who is a passionate coder along with an intelligent statistician and for statistics, there is nothing as good as R. Because of its power of statistics, R is also called as the golden child of the data science. The data scientists skilled with R are being looked upon by the biggest brands like Facebook, New York Times and Google, etc.

Some of the major reasons why you should learn R are as follows:

• R is freely available: Unlike other languages like SAS or Matlab, R is free to install and use. You need not buy any premium license to use it.
• R is an open-source programming language: Using R is free and it is available to update, modify and redistribute as well. You can get your own version of R and resell in the market.
• Easily upgradable: R allows for easy upgrades which are essential for any statistical language.
• Cross-platform compatible: You can run R on any platforms including Mac OS, Windows, and Linux, etc. the data can easily be imported from other components like Microsoft Access, Microsoft excel and Oracle etc.
• Powerful scripting language: R is capable of handling complex and large data sets. It can be perfectly used for heavy simulations. Also, you can use it for high-performance clusters of the computer.
• Widespread use: R is one of the top programming languages of 2019 and an estimate of 2.5 million users use R.
• R is highly flexible: R is flexible enough to use and most of the new developments in statistics are in R.
• Publishers like using R: R can be easily integrated with systems like Latex which are used for document preparation.
• Huge R community: R has a vibrant community with many users who interact on a daily basis.

If you are interested in learning R, Compufield is the recommended institute to take up the offline classes in Mumbai.

Why choose Python?

Another best programming language for professionals who want to enter the world of Big Data in Python. It is a high-level programming language and easier than R to learn.

Read more to know why to opt python:

• Easy to learn: The syntax of python is very easy to learn and understand.
• User-friendly language: With less code to write, Python acts as a user-friendly language with features like code readability, ease of implementation and simple syntax.
• Easier to debug: With less code, it becomes easier in python to debug the code. Python compiled programs are less prone to bugs and errors.
• Widely used: Python is used in various industries like YouTube, Google, Quora, and Reddit, etc. Being skilled in python, you can get a job in any of them easily.
• Object-oriented language: You can easily migrate to any other OOP language if you know python well.
• Open source: Python is open source and can be used for free.
• High-performance language: The faster web applications are widely built in python.
• In-built libraries: There are many inbuilt packages and library in Python which can be used for complex functionalities.

If you are planning or interested to learn python, one of the best institutes is Peta Bytes, offer Python training in Mumbai and also provide online training all over the world to get the best knowledge on Python.

Why Hadoop?

If you are planning your career in big data, another very important and widely used language in Hadoop. Need to know why to have a look below:

• Open source: Hadoop is open-source the same as python and R. Thus, it has the flexibility of use.
• Powerful language: A huge amount of data can be easily stored and processed in Hadoop. The capability of it has impressed users in many organizations. For large enterprises, Hadoop has become a must to have the technology.
• Many opportunities with Hadoop: Being a skilled professional, you can get many roles with Hadoop including Hadoop administrator, Data scientist and Hadoop developer, etc.
• Versatile: Along with warehousing data, it can be used for data discovery, analytics, and ETL, etc.
• Increase in demand: With time, the demand for Hadoop in increasing in top MNCs likes Dell, Yahoo, Google, and Facebook, etc.

10 Reasons You Should Learn R, Python, and Hadoop

Data Analytics Domain continues to excel at Software as a Service, or SaaS companies, as we popularly know it. Everyone wants to break into Big Data and they have a lot of job opportunities on the rise. But making taking a step forward into Data Sciences it is imperative to understand what it is and which Data Science Certification to opt for. This is where R,  Python  and Hadoop come in and here are ten good reasons to know them. These are basically programming languages that need to be learnt to break into the data sciences industry, which includes top names like Google, Bank of America and The New York Times.

1. 1. Availability: How is a new user supposed to learn them? R, for example, is free to install and run and that gives the user the independence to sit and learn about it anywhere. Python, on the other hand, is easier to learn and some say it is the easiest of programming languages.  Hadoop Certification , is again, available on open source networks, which makes it easily available. Depending upon your convenience, the user can use any of them.
2. 2. Easy Upgrades: As far as data analysis is concerned, these three open- source programming languages are the most popular. Data import visualization, MapReduce and Parallel Processing can be best achieved with them, as a result of which the integrated analysis platforms have to be constantly upgraded, which is again made easier by them. 
3. 3. Cross Platform: The programming languages can all be used across multiple platforms, like Windows, Mac OS X, Linux and a few more, allowing the users to get their work done on any device. R and Python developers are now coming up with ways to deal with larger data sizes across larger platforms, and working on both SQL and NoSQL databases.
4. 4. Complexity made Simple: These three programming languages are used for handling large and complex data, otherwise known as Big Data. Heavier and complex simulations can be done in relative ease by using these languages, in high performance clusters or with multiple processors. Python reads data better than R but both communicated well with Hadoop, giving the users the option of relying on other factors to choose which one to go with.
5. 5. Great Acceptability: With so many benefits, the languages have gained widespread acclaim and about 2 million users use them worldwide while dealing in data science. Already R has gained widespread acceptability with  Oracle , SAP, Netezza and Teredata have started developing interfaces that uses R as an analytic support.
6. 6. Statistical innovations: Any new developments of software upgrades always take place in one of these three languages because they are the most evolved and flexible. With new innovations like ff and bigmemory, it is now possible to deal with datasets larger than memory. Python reads data much more efficiently and synchronization with Hadoop is an added bonus.
7. 7. Ease of Publishing: Since the programming languages integrate well with document publishing, they are the publisher’s favorite. Smooth assimilation with LaTeX documents publishing system as well as the feature of being embedded in word processing documents is a huge plus point. All the languages have pretty large ecosystems, making it easier to publish and handle large volumes of data.
8. 8. User Friendly: R, Hadoop and Python are user friendly and supports the import of data from Microsoft Excel, Access, MySQL, SQLite and Oracle, allowing any user with any software to function without hindrance. Python has been effectively used for Natural Language Processing and Apache Spark has made the data found in Hadoop clusters all the more easily accessible.
9. 9. Networking: Community links and networking is a vital part of any global organization and passionate users are always connecting over forms to discuss these languages more than anything else, ensuring a seamless exchange of positive information. The newly launched Anaconda parcel already has more than 300 plus packages that has garnered rave reviews from users worldwide in their forum, egging them on for future packages.
10. 10. Easy Debugging: Scanning and debugging is easier with these languages than others because most debugging tools are made in compliance with these languages, allowing users to set things right with greater efficiency. Every language has its own pros and cons and yet it can be said that R, Pyhton and Hadoop configurations are the best you can use to keep your systems safe and the best option if you have to go for a complete system overhaul.