Why Python Training is Essential for Big Data Jobs

Introduction:

1. As we know that the Python is an open-source, portable, extensible Platform nowadays for most corporates as well as for industry which is being used for automating deployment, scaling, and management of applications. 
2. Among all the programming languages the Python is being considered the most versatile and popular programming language.
3. It was created by Guido van Rossum, in the year 1991. 
4. In the present cut edge of technology, Python is a more powerful language that offers great tools for data crunching and preparation, as well as for complex scientific data analysis and modeling.
5. It also supports complex scientific data analysis and modeling.

Need of Python: 

As we have already discussed above that the Python is a more powerful language in the present scenario, which offers great tools for data crunching and preparation, as well as for complex scientific data analysis and modeling. It has a great feature and enriched collection of libraries with itself. In addition, with this it is also used for the following purpose.

• Server-side web application development
• Application software development
• The mathematics and Analytics
• System scripting

Python as a most versatile Language

In other words, we say that Python is more popular language. It is having the simple syntax and gradual learning curve has been one of the most popular reasons as to why it’s used in Big Data.

Python for Big Data:

When we are moving towards the Big Data then Python is considered as a best choice for most of the developer. As we have already known that the Python language is used to have an enriched collection of libraries which enables the high computing mechanism.  Also, if we can see the history of languages, then among them the Python is used to have more flexibility and features then others.

As the technology now a days gets more and more competitive, data scientists and engineers are continually striving for ways to process information, extract insights and model, by processing massive datasets. 

It is having the following features which makes it so popular for the Big Data computing, such as

1. These are open-sourced libraries, offering alternate ways of deriving the same output. 
2. Python is the only platform where we can be able to explore all the constraints in more efficient way. So, you need to be well versed in the various Python libraries that support your data science tasks and the benefits they offer to make your outputs more robust and speedier.
   

It would be interesting to know that interns in organizations are actively engaged in teaching the language to new employees. 

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“Hadoop” the technology for Big Data:

If we are considering the Python environment then using Python, we can be able to build a framework that makes it easy for us to grab data from all of these disparate data sources and model them. 

So, instead of everyone spending their time writing database connector code, they are able to use a simple configuration and quickly get off the ground”.

In the nutshell concept, the Hadoop is having the best architecture which enables the data segregation is complete sense. It is used to have the following feature which makes it unique with respect to other available options in the market. When we are going to relate the same with Python then the Python is used to provide the complete data segregation which will help the developer to analyse the data perfectly and accordingly, they could be able to code.

Python as a true Solution 

1. Python enables the writing of the Hadoop’s MapReduce programs and its related applications for accessing the HDFS API for Hadoop with PyDoop Packages is more effective way as it has a complete set of libraries.
2. The PyDoop, is basically an application package tool kit provided by Python open community which provides a sophisticated Python API for managing the Hadoop’s MapReduce and HDFS. 
3. It is being considered as the link interface between Python and Big Data.
4. PyDoop has many Hadoops supported built-in solutions and providing the better option for Hadoop Streaming using Python programming.
5. In PyDoop we can be able to connect an HDFS (API for Python) installation, read and write files, and get information on files, directories and global file system properties.

Python as a tool kit:

Python language is now becoming the only platform where we can be able to explore the various domains of problems in efficient manner. So, you need to be well versed in this area and you need to understand the Python libraries also. As of now the Python is used to support our data science-based application tasks and used to provide the major benefits.  It is used to offer more robust and speedier way for developing the applications and thus becomes more popular within the less span of time. It has many applications areas out of which I am going to discussed few listed below.

• Web Development.
• Game Development.
• Scientific and Numeric Applications Development.
• Artificial Intelligence and Machine Learning based application development.
• Software Development based application development.
• Education programs and training courses. 
• Language Development.

What is BIG DATA?

Trending of Python as on today:

Due to its unique ability of Python, it is already a proven language in the industry. It supports many standard feature and enriched library, so it is widely being accepted now a days by most of the industry, corporates and in education sector. As of now it has already taken the lead as the toolkit for scientific data analysis and modelling. 

As I have already discussed earlier that the Python is having the great features which makes it unique then other programming language, so it became a major part of the Job seeker prospect also. For a developer prospect also, it is very much trending now a days as it provides the following advantages Such as

• Python can be used on a server to create web applications and enables the software to create better workflows.
• Python can connect to database systems in simple manner as it has the toolkit for it. So, the developer need not require to write a toughest code for that. It can also use to read and modify files in efficient manner.
• Python can be used to handle big data and perform complex mathematics and support the concept of rapid prototyping, or for production-ready software development.
• Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc).
• Python runs on an interpreter system, and its syntax is very simple and lucid which allows the developers to write programs with fewer lines than some other programming languages.
• Python can be treated in a procedural way, an object-oriented way, or a functional way.
  

Python as a Big Data Job Prospect:

Looking to the present market scenario the market is become very competitive. On the other hand if we analyse the Utilisation Chart for Python in the series of year then we can see that the Demand of Python has increases rapidly among the developer. 

As per the job trends on Indeed.com, the Python language is being considered as a best option for Big Data based problems. It has the plenty of enriched library with sophisticated tool which minimizes the developer burden up to grate extent. Hence many companies are now looking for Big Data analytics, python training seems to be a must on your resume. 

Python is vastly powerful for solving complex and difficult data analytical problems in virtually any domain. Python is platform independent, and so it can integrate with most existing IT environments. Python has high capabilities for Big Data manipulative tasks and its natural strength as a scripting language makes it highly adaptive for data–oriented applications.

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