Analytics using Python is gaining popularity across industries

Python has been securing its place among the top three general purpose languages since 2016. One can infer easily that it has a great many important features. The more is that Python has developed into a vital tool for data analytics.  it has remained extremely popular among analysts and data scientists because it is an open source, general purpose programming language, which is extremely flexible and has ease of use.

Since Python has a rich set of libraries it becomes very useful for programmers. Python big data analytics is here to stay and it is imperative that you sign up for a course without delay.

Reasons why Python is a market leader over other programs

There are several other big data analytics tools like R, SAS, Hadoop, but why the importance and relevance of Python remain unabated.

  1. Python can be computed with the least number of codes; thus, it is easier to comprehend.
  2. Python is highly compatible and can be easily integrated with other programmes.
  3. It is much easier to grasp than other analytical languages. Thus, first-time users find it easier to maneuver. And, since it has an extensive community, it gets easier to discuss and solve any problems.
  4. It has some powerful inbuilt packages, like- NumPy, Pandas, Scipy, Scikit learn, PyBrain and several other important libraries, which comes to great use for data scientists and analysts
  5. Python has great data visualization tools which help create a great graphic representation of the data under consideration.

Python in the banking industry

The volume of data generated in the banking industry is humungous, and by using big data analytics, the banking sector can increase their customer base with personalized insight into the individual client. Financial technology is the new arena for growth and development, and python is the dominant player.

By using comprehensive data analysis, banks can minimize the risk of errors and fraud, and provides easier filing of regulatory compliances, thereby providing effective customer services.

Python big data analysis in the telecom industry

Telecom industries harness the huge amount of data, and they require proper analysis of the structured and unstructured data that is generated. Thus, it will help them to gain insight into their customer usages and provide for personalized plans, thus, keeping them ahead of their competitors.

It also helps stall data fraud by understanding the data usage and by understanding the customer concentration; they can cater to region-specific advertisements thus attracting more clients.

Conclusion

The usage of python in big data analytics is infinite. Every industry requires analysis of all the data that is generated since, without it, it becomes just random information. To derive cohesive components from the data deluge is the job of big data analysts. And the preferred tool in this important work is – the ubiquitous Python.

If you are planning to venture into the world of big data analysis, then you would need to master Python. For a beginner too, Python is easier to understand than any other language.

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