We as humans are very found of comparisons to help us choose the best prom the bests. Whether it may be iOS vs Android or Nike vs Adidas, there is a comparison in almost every field. So it is in the data industry.As the Digital world is thriving at a greater acceleration, the need to store data is on the rise. The data accumulation is at the forefront for many businesses to enhance their growth. It is therefore very essential to keep the data structured and organized si it becomes easy to use.R, Python, and SAS are the three major programming languages used to filter data and help in the organization of the same.All three major languages do the work efficiently according to the needs and are centralized to a more specific approach.
R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.
Python is an object-oriented programming language that has clear syntax and readability. It was created in 1991 by Guido Van Rossem. It is easy to learn and will help you work more quickly and effectively. It has become more popular in a short period of time because of its simplicity.
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. But, it is not open-source and ends up being an expensive option for a beginner.
1 . Cost:
Cost is the major factor contributing to our decision to benefit from the product. R and Python is open source and completely free. They don’t charge anything and are free to access. SAS is expensive software and only private companies can afford it. This doesn’t take away the benefit it provides to the users. It is the leading analytics software used by major companies such as Nestle, HSBC, etc.
2 . Ease of learning:
R is difficult to grasp language. You cannot learn it without having a prior understanding of coding. It has a very tedious process. Even a small mistake while implementation makes the task complicated. Python is renowned for its simple use and learning the language. It can be usually accessed by beginners as well as data scientists to lean it. SAS is the easiest to learn among the three. It comes with a GUI that assists in learning. Moreover, you can learn fro the tutorials it provides.
3 . Data handling capabilities:
R computes everything based on the RAM. So if you have a relatively low storage RAM, you will be able to handle data according to it. This is no longer the issue. Python and SAS are both equally good in managing the data. We can conclude all three are at the same level when it comes to data handling. They all have the option of parallel computations as well.
4 . Graphical Capabilities:
When it comes to graphical capabilities, R is the leader. It has a very dynamic and easy to use graphic interface. Python is par with R due to its unique graphical packages such as VisPy, Matplotlib. It is more complex when compared to R though.SAS has a basic graphical capability. However, it is purely functional. Any customization needs an understanding of the SAS graph package thoroughly.
5 . Updates:
R and Python being open-source provide new updates faster. They give new techniques and features frequently. SAS, on the other hand, provides new developments a little late when compared with the two. But due to working in a well-controlled environment, the new developments and features are well tested and error-free.Being open-source, the R and Python updates are generally error-prone.
6 . Customer Support:
R and Python being open source do not have a team specifically concerned with customer support. So if you have some issues to be resolved, you have to do it for yourself.But, they do have a big online community. So, if you face some problem, you can reach to the community for help. SAS has a special team dedicated to effective customer service. You can any time reach out to them and you will be answered. It provides great technical support.
All three come up with its unique features and are best according to what you need to get the benefit of.It all depends on the field and work you want to do If you want to keep a tap on data analytics for a big IT company, SAS is the best option as they can afford the huge cost.If you are just starting, Python should be your go-to option due to it’s easy to understand learning, a large community. As R has a stronghold in calculations, it is a very good option for statisticians and researchers.