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People who wish to embark or make a career shift in coding, or have a passion for coding always find themselves standing at crossroads with the dilemma of choosing the most appropriate programming language. Coding is an essential skill set for any data scientist or a professional working in the data analysis field. SAS often comes as the most preferred option in programming languages. Specially, if you are beginning your career, then this is the most obvious and logical thought to have.
Is SAS the right language to learn? Is knowledge in SAS enough to start your career in data science and coding? SAS v/s R or Python which is best? few questions you should have answers to.
As a general answer, there is no language in programming that can be termed as ‘Best’ purely because it is knowledge that you are acquiring, the same knowledge can be transferred.
All programming languages are good and developmental. Learning a programing language can be compared to driving, if you take the analogy further, you learn driving a particular car, but later you can apply the same skill while driving a truck, or a tractor, or an automatic vehicle, left hand or a right-hand drive. In the same way, all programming languages implement, Input, Output, Variables, Loops, Conditions, and Functions.
Learning one language will make learning the other one simpler, it is majorly only a different Syntax.
SAS is popular and can be considered as the undisputed market leader in the enterprise analytics scenario, it has a good GUI hence learning becomes fairly structured and easier. It has a good array of statistical functions and also offers great technical support.
SAS is majorly popular in established organisations because they are synonymous with great customer support and service. SAS is an expensive tool, therefore in the financial sector, where a budget is not a concern, it is usually the preferred option.
For these reasons SAS is still considered a leader in the coding sector by dominating 80% of market and R and Python together at 20%, they are open source languages.
However, on conducting a survey with over 1000 quantitative professionals, on mapping their preference in programing language, only 39% of them voted for SAS, while 42% for R and the rest 20% for Python.
Retail, Marketing and majorly Healthcare, Pharma and Financial services are loyal to SAS, while Telecom and the Corporate Start-up sector, swings towards R and Python. These sectors have large volumes of unstructured data, machine learning techniques need to be applied, for which R and Python are more suitable.Data Analytics Banner
Cost of learning is also one of the factors while making an informed decision. SAS is very expensive when compared to other languages, so unless your company is assisting you in training, on an individual level it’s a costly affair. Although expensive SAS is fairly easy to learn, plus you do not need any prior knowledge in programming, basic SQL knowledge is good enough.
With SAS it will be easy for you to get a job, it is a fourth generation language, it relies on user-written programs, that when requested know what to do. Based on your needs and interests, it can be said that SAS is versatile and flexible with a variety of input and output formats. SAS has an electronic network where resources are available and one can get connected to share knowledge.
One needs to base their decision on personal factors, if your dream is to join a start-up or the telecom sector, then perhaps R or Python should be your choice. If you want to join the financial sector or venture in healthcare, then maybe SAS should be your first preference before learning any other languages.
 

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