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Importance of Python for Big Data Analytics

International Statistical Report by Statista suggests that every day over 1 million users register on WhatsApp, and the number of active users of WhatsApp is more than 1.5 billion. Around 65 billion messages are sent, and more than 100 million voice calls are made every day. Data is exploding rapidly; executives even predict the generation of data is likely to grow by 52% in the next two years.

The growing data is unstructured and is available in various heterogeneous formats. These vast volumes are known as big data and analyzing this data structurally is known as big data analytics. Many scientists and researchers are working in this domain by using various tools and technologies.

Importance of Python for Big Data Analytics

Python for Big Data

There are many ways to obtain data for R&D; the first is to obtain data from open data portals and the second is to generate personal data sets using different programming languages.

Using programming languages to get data is the prominent method utilized by data scientists nowadays. However, a bigger challenge is to set the appropriate language for fetching the live streaming data as most languages prove ineffective in this endeavor.

Python has emerged as one of the most outstanding programming languages that can communicate with various live streaming servers. One can also use it to store the fetched data in the file systems or databases for predictions based on proper analysis. Due to these reasons, Python is now the most important programming language to learn for people who want a career in data analytics.

Stats suggest that there will be a 160 percent rise in data analytics jobs in the next two years. So, if looking for a career in data analytics one can opt for online lectures or regular classes of Python course in Delhi or Chennai according to their preference and take the first step towards a bright career in data analytics.

Reasons Why One Should Learn Python for Big Data Analytics

#1 Minimum lines of Code

Python programming is known to work efficiently in the least lines of code. It can automatically identify and associate data types and follow indentations on the basis of the nesting structure. The time and effort taken to understand and develop coding in Python are less than other programs, and there are no limitations to the processing of data in it. One can easily compute data in laptops, cloud, commodity machines and many other devices. Python is fast in both development and execution; thus, becoming the first choice for data analysis.

#2 Compatibility with Hadoop

Hadoop is the best open-source big data platform in the market. The compatibility of Python with it is another major reason why organizations prefer Python over other programming languages. Packages in Python offer access to HDFS API for Hadoop through which applications and MapReduce programs can be easily written. One can also connect their programs to HDFS installation and make programs easy to write and read. The MapReduce API can easily solve complex problems with minimum efforts making data analytics seamless.

#3 Robust Packages

Python has a set of robust packages that can handle a wide range of analytical and data science needs. Some of the most popular packages are:

  • Pandas: A library for data analysis that offers a wide range of functions that deal with operations and data structures such as; manipulation of numerical tables and time series.
  • PyBrain: Short for Python-based reinforcement learning, artificial intelligence and neural network library. It offers algorithms for machine learning along with the capability to test the algorithms in different environments.
  • NumPy: It is used for scientific computing and is great for operations related to Fourier transforms, random number crunching and linear algebra.
  • Scipy: It is a library for technical and scientific computing. It contains modules for data science and other tasks like interpolation, signal processing, FFT and ODE solvers.

#4 Data Visualization

Python is one of the best programming languages when it comes to data visualization. API’s like Plotly and various libraries like ggplot, Pygal, NetworkX etc., can help in creating amazing data visualizations. Popular big data visualization tools like Tableau and QlikView can also be integrated into this programming language.

The popularity of Python is gaining grounds with increasing speed. A person with good knowledge of Python can find lucrative jobs in various sectors like research & development, customer service, maintenance and others. Large enterprises are looking forward to hiring people with good knowledge of Python as it bodes well in establishing good communication between various departments.

Therefore, start your journey in the world of data analytics with a good knowledge of Python programming. To take the best first step, join Python course in Delhi or Mumbai and learn from the experts.

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About the author

Charmin Patel

Blogger and Digital Marketer by Choice and Chemical Engineer By Chance. Computer and Internet Geek Person Who Loves To Do Something New Every Day.

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