Leveraging the Power of Python to Process Big Data

As a number of recent surveys have highlighted, Python is the most popular coding language of 2015. At the same time, Python is also rated as one of the most efficient programming languages for processing large, complex and hardcore data. As a high-level programming language, Python enables programmers to express concepts by writing less and readable code. The highly extensible design of Python further makes it embeddable with existing applications as a programming interface. There are also various tools that help businesses to process and analyze large-scale data by leveraging the power of Python.

Why Python is used widely by Businesses for Big Data Processing?

Solid and Powerful

As noted earlier, Python enables developers to express concepts without writing longer lines of code. Also, it supports several programming principles including object-oriented, imperative and functional programming. The feature makes the programming language robust, solid and powerful. So developers can use Python to write clean, readable and less code. In addition to being easier to debug and maintain, the smaller quantity of code is also less prone to issues. Also, the programming language is fast enough to optimize the data-driven applications’ functionality and performance.

Highly Flexible

Python is more flexible and scalable than other programming language. In 2007, YouTube migrated to the object-oriented programming language to accomplish higher scalability. The flexible nature of Python further makes it usable for building a wide range of applications including websites, internet apps, desktop applications, Voice over IP, and system administrative. The developers also have option to use a variety of Python tools to rapidly develop scientific and numeric application. Thus, Python makes it easier for businesses to create data-driven applications for different devices and platforms.

Easy to Use

Despite being powerful and flexible, Python is easy to learn and use. Many software developers even choose Python as their first programming language. Unlike other programming languages, Python does not require learners to look for references frequently. Further, the simple and straight-forward syntax of Python makes programmers adopt several good programming practices. That is why; the business analysts and managers can learn and use the programming language without putting any extra effort.

Works with Existing IT Infrastructure

Python is available for major operating systems including Windows, Linux, UNIX and Mac OS X. The developers can further execute Python application development code on multiple platforms simply by installing specific Python interpreter. So businesses can use Python regardless of their existing system. At the same time, Python-based solutions can be integrated with the business’s existing IT infrastructure. As Python can be used for creating a variety of data-driven applications, it becomes easier for enterprises to process hardcore data without investing in additional systems.

Tools to Process Large-Scale Data

In addition to being a powerful programming language for large-scale data processing, Python also benefits from various toolkits provided by the rich data community. Some of these tools can be used by programmers to effectuate the processing of large-scale data, whereas others can be used for interpretation and analysis of data. For instance, the Python programmers have option to use large-scale data processing and wrangling tools like PyTables, Pandas, PySpark, Disco Project, and Python API for the Spark data analytics framework. Likewise, they can effectuate large-scale data analysis by using tools like scikit-learn, scikit-image, and Augustus.

Reduces Time to Market

A number of reports have highlighted that enterprises prefer using open source programming languages to reduce time-to-market. As a dynamic programming language, Python can be used for building mission-critical enterprise applications for various domains. Python also comes with a huge standard library to reduce the software development time significantly. The developers also have option to write code in other programming languages, and integrate it with the Python code to fast time-to-market for the applications.

The effectiveness of Python to process big data can also be determined by its popularity among large and reputable organization. Python is currently being used by several reputable institutions including JP Morgan, Bank of America Merrill Lynch, ABN AMRO Bank, Treasury Systems, and Altis Investment Management. However, the small businesses and startups can also leverage the power of Python for big data processing, as it is an open source programming language.

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