Python vs SAS vs R

As the dominance of the digital world has increased, there is an insignificant increase in data being stored. You choose any subject and you can find data on it. The disadvantage is that all these data are not structured. So, to make it useful, these data need to be mined and interpreted. There are several programming languages like Python, SAS, and R to filter the data and make them useful. Many giant IT companies rely and operate on data analysis. 

As the demand for data analysis is growing quickly, the market demand for data scientists has also grown enormously.  One should know at least one of the programming languages used for data analysis to give their career an edge in the IT industry. 

Python vs. SAS vs. R, all three do an excellent job on the platforms they have set out. To choose amongst them and decide which one is better is a very difficult task. Each has its own set of features that are unique in its own way to curb various requirements.   

However, for professionals who want to build their careers in data science, we have provided exclusive comparisons between these 3-programming languages. 

Before starting comparisons, let us first understand all 3 technologies.

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Data Science Python Vs SAS Vs R

What is Python?

It is an interactive and interpreted high-level object-oriented programming language. It is known for simplicity and clear syntax which in turn increases readability. It is easy to learn and understand. It is largely used as an open-source scripting language that supports many libraries used for model building or statistical operation on data. It is used by many biggies like Google, Quora, Reddit, etc.

[ Related Article: Python Tutorial for Beginners ]

What is SAS?

SAS has been proved as one of the unchallenged leaders in the field of data science. It is known for its huge variety of statistical functions, good GUI, and great technical support experience. It is also easy to learn. SAS is used by various IT companies like Nestle, Barclays, Volvo, and HSBC. But, it is not open-source and ends up being an expensive option for a beginner.

[ Related Article: SAS Tutorial - A Complete Guide ]

What is R?

R is a counterpart of SAS and is free as it is an open-source platform. It is mainly used in the academics and research section. As it is open-source, it is highly extensible and there are quick releases of the software with the latest techniques. You can find multiple information sources for R over the web.

Comparison Factors: Python vs R vs SAS

Let us now compare some factors of Python, SAS, and R to choose the best which suits your requirement.

1. Cost-Effectiveness:

7. Application Advancements:

Conclusion

R has a slightly steeper learning curve compared to SAS and Python. Since R is a low-level programming language, it requires proficiency and basic programming orientation. If not correctly implemented, even minor tasks will become Herculean and involve complex code lines. Its overall learning can be considered as average to high.

Currently, there is a slight bend for Python in the job market. But due to the dynamic nature of the IT industry, we cannot determine which programming language is better. It totally depends on the requirement specifications and factors like the learning phase and cost. 

Below are some cases where we can guide you in choosing the language. Go through it and select whichever is more suitable to your specifications:

• For a freshie aspiring to make a career in data analytics, SAS is the best priority as it is simple and still tops in the market
• For experienced professionals, we recommend learning any 2 of these will open a path for better job opportunities.
• For the one who is willing to work in start-ups or as a freelancer, Python is a must.

If we need to divide these languages over a specific category, then these would be defined as follows:

• All big IT organizations choose SAS as their data analytics tools
• As R is very good with heavy calculations, it is largely used by statisticians and researchers. 
• Startups prefer Python over the other two due to its lightweight nature, large community, and deep learning capabilities.

Now, we hope you got a clear idea about all three languages and believe this knowledge will be helping you to choose the best programming language for your career advancements.

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