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10 Reasons Why You Should Choose Python For Big Data

Leo Migdal
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10 reasons why you should choose python for big data

Big Data is the most valuable commodity in present times! The data generated by companies and people is growing so much that the data generated would reach 175 zettabytes in 2025 whereas it is around 50 zettabytes currently. And Python is the best programming language to manage this Big Data because of its capacity for statistical analysis and its easy readability. Well, there are many more reasons that contribute to the success of Python. One of these is its library support for data science and analytics. Many top companies such as Google, Facebook, Mozilla, Quora, etc.

use Python for managing their data. But let’s study all these reasons in detail to understand the popularity of Python and its astounding growth rate in Big Data Analytics. Python is an open-source programming language that you can use for free. In fact, you can download the recent version of Python directly from their official website python.org. And Python is easy to learn as well! It is simple with an easily readable syntax and that makes it well-loved by both seasoned developers and experimental students.

The simplicity of Python means that Big Data Engineers and Data Scientists can focus on actually managing the big data and obtaining actionable insights rather than spend all their time (and energy!) understanding just... That’s one of the reasons to use Python for Big Data! Python is very scalable in handling large amounts of data which is a necessity where Big Data is concerned. Other programming languages that are used in Big data Analytics like Java and R are not as flexible and scalable when compared to Python. If the data volume is increased, Python can easily increase the speed of processing the data which is tough to do in Java or R. Python is also extremely flexible.

and supremely efficient. It allows developers to complete more work using fewer lines of code. The Python code is also easily understandable by humans, which makes it ideal for Big Data analytics. Python is already quite popular and consequently, it has hundreds of different libraries and frameworks that can be used by developers. These libraries and frameworks are really useful in saving time which in turn makes Python even more popular (That's a beneficial cycle!!!). Many Python libraries are specifically useful for Data Analytics and Machine Learning.

These libraries provide a lot of support for handling Big Data which is one of the reasons for choosing Python for Big Data. Some of these libraries are given below: Choosing a programming language over another in the big data field is very much project specific and depends on the project goal. However, whatever may be the goal Python and Big Data is an inseparable combination when we consider a programming language for big data development phase. It is a crucial decision because once you start developing your project in a language, it is difficult to migrate in another language. Moreover, not all big data projects have the same goal.

For example, in a big data project, the goal may be simply manipulating data or building analytics while in others it could be for the Internet of Things (IoT). Also CHECK: Python for Beginners – A detailed Course with FREE hands-on labs Furthermore, Python is not limited to big data only and widely used in other technical fields as well which adds its usefulness. IEEE Spectrum has also ranked Python as the number one programming language. In this blog, we will discuss on few reasons why Python and Big Data combination is a favorite choice for big data professionals. Python is a general-purpose programming language that enables programmers to write fewer lines of code and make it more readable.

It has scripting features and besides that uses many advanced libraries such as NumPy, Matplotlib, and SciPy which makes it useful for scientific computing. Updated on Nov 24, 2025 | 7 min read | 6.73K+ views Big Data is a massive collection of data that is growing exponentially over time. It is a data set that is so large and complex that traditional data management tools cannot store or process it efficiently. Big data is a type of data that is extremely large in size. Python is the ideal programming language for Big Data due to its ease of use and statistical analysis capabilities.

Python is a rapidly growing programming language, and a combination of Python and Big Data is the most popular choice among developers due to its low coding requirements and extensive library support. In this article, we will look at the Top 10 Reasons to Learn Python for Big Data. Python programming requires fewer lines of code when compared to other programming languages. It can run programs with only a few lines of code. Furthermore, Python provides automatic assistance in identifying and associating data types. Choose Python for its simplicity, power, and vast ecosystem.

by Michael CardozaSep 12, 2024Development So, you’re embarking on a new coding adventure and staring down the endless choices for programming languages. Let’s cut to the chase—Python is the one. Think of it as the comfortable pair of jeans that somehow looks good in any situation. Whether you’re building the next big app, crunching data, or just automating your coffee machine, Python’s got your back. Python is a general-purpose language that supports multiple programming paradigms, including procedural, object-oriented, and functional programming.

This versatility allows it to be used for a wide range of applications, such as web development, data science, machine learning, automation, and more. Python comes with a vast standard library that includes modules and packages for handling everything from file I/O and regular expressions to web services and data manipulation. This reduces the need for writing code from scratch and speeds up development. Hi White Ninja, Thank you for your positive feedback. We hope that you will find our blog useful in future as well. Keep visiting the Edureka Blog page for latest posts on this link: https://www.edureka.co/blog/

Python is one of the most popular programming languages today because it is easy to use and very flexible. You can use Python to build websites, create smart AI programs, and study large amounts of data. Its simple style helps beginners learn quickly, and it also has strong tools for experienced coders. In this article, we will look at why Python is popular, who should learn it, what it can be used for, and how it can help you start a great career in tech. Python is now one of the most popular programming languages. People use it to build websites, create smart AI systems, and study data.

It is easy to learn and use. It also has many helpful tools and a big community to support you. These things make Python a great choice for new learners and skilled coders. Before looking at the top 10 Reasons Why Python is Popular, let’s check out who should learn Python programming. As we have learned about why Python is popular, now let's understand who can learn it. So, Python is a great choice for many people who want to learn new skills or start a new job.

If you are a beginner, Python is easy to read and understand. This makes it simple to learn basic coding. Python has powerful tools to help you do your job faster and better if you already work in data science, web development, or AI. Teachers and researchers can also use Python to study data and make charts. In short, if you are interested in coding, solving problems, or working with data, learning Python is a smart idea in today’s tech world. Python is simple as well as easy to understand.

Its code looks like plain English. This helps beginners learn it quickly without confusion. You can also use Python for many things. It helps build websites, study data, and make smart AI systems. Many tools like Django, Pandas, and TensorFlow make these jobs easier. This term becomes viral in the big data industry.

There are several programming languages and big data tools to analyze the raw data with different tactics. But, why python is creating hype in data analysis? This is what we gonna see in this article. Here we are going to cover the usage of Python in big data, in different verticals, Like why choose Python for big data projects, what are the top 13 reasons to choose Python for... Before starting to explain why use Python for big data, Let us have a short intro to Python. Python – As by its definition, it is an interpreted and general-purpose programming language.

So using Python we can develop advanced desktop applications, web applications, websites, mobile apps, and more. Mr. Guido Van Rossum invented Python to overcome the flaws of the farmer programming language ABC developed by CWI(Centrum Wiskunde & Informatica), Netherlands. Python has several specialties like dynamic typing, and dynamic binding in order to proceed with Rapid Application Development. Python can be used to develop any kind of application. But, in the big data industry, python provides better involvement, benefits, results, time efficiency, and ease of access than any other languages like R, Java, and more.

Choosing Python in big data is highly project specific, and meets the project goals on time with no big huddles. The most unavoidable risk of big data is industry, “migrating the entire project to another language”. Python brings higher efficiency and provides us an option to easily migrate any big data or data science projects into the desired programming language at any time. Many developers and experts point out that Python is the most suitable programming language for technology projects like AI, IOT and more. Python is not only favoring the developers alone but also favors business in terms of fulfilling the project goals on time. Likewise, we can list out N number of powerful use cases and benefits of Python in big data.

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