In this blog, I’m going to share with you the best ever battle between SAS Vs R. To find the difference between SAS vs R is always an overwhelming task for the statistics students. But today, I’ll show you which one is better statistics language and why? Let’s dig in:-
The statistical analysis system is known as SAS. It is one of the significant statistics tools in the world. It is used in a large organization that why it is called the business analytics tool.
It helps the business in its operations; likewise, it helps the companies in data management services and business intelligence capabilities. I called SAS as one of the best statistics tools the reason is it helps the company to get insights from the raw data or from any material that contains the information.
Majority of big enterprises use SAS to perform analytics operations on various components of the business. It is a licensed one. If you would like to use R, then you should have the basic knowledge of SQL. It is used to output the statistical analysis in table and graphs which is processed from spreadsheets and databases.
The significant use of SAS is in financial analytics. It also offers the full range of statistical functions and also provides the best GUI for data analytics applications deployment. As I mentioned earlier, it is easy to learn, but it is quite expensive as compared with R.
R is an open-source programming language. It is a low-level programming language. That’s why it is used in used for research and academic purposes. R get the latest updates on regular intervals.
R language is specially designed for statistics operations; that’s why all its methods are statistical and graphical. R is still a popular language lots of MNC are using R in their organization. Uber, Google, Facebook are the top among them.
R also provides the flexibility to communicate with other languages too. It is more potent than SAS, but it is quite challenging to master R as compared with SAS.
Some of the R application are
- Used in Finance process and market.
- The data importing, cleaning functionality.
- Playing a crucial role in data science.
Some of the SAS applications are
- Predictive analytics
- Business intelligence
- Prescriptive analytics
Feature of R
- Ability to connect with various databases and data types
- Provide complete statistics flexibility using a large number of algorithms and packages.
- Ability to collect and analyze social media data.
- Use for prediction in data science.
- Scrape data from various websites.
- Integrating with other languages
- Great data visualization platform.
Features of SAS
- Project Management and operation research
- Report formation with standard graphics
- Data updating and modification
- Powerful Data handling language
- Read and write any data format
- Best data cleansing functions
- Ability to interact with multiple host systems
Parameters of Comparison (SAS vs R)
Ease of Learning
Undoubtedly SAS is easy to learn a programming language. If you want to learn a new tool without having any knowledge or experience with the programming language. Then you should opt for SAS.
SAS allows us to analyze the SQL code, macros integration, and so on. If you have a basic knowledge of SQL, then you can learn SAS quickly. But if you’re a beginner, then it will also be an excellent experience for you to learn SAS.
R is a low-level programming language. That’s why it is a bit harder to learn R as compared with SAS or any other programming language. If you’re going to learn R, then you should have a basic knowledge of programming.
It is quite hard to work with a low-level programming language. Because a small problem can turn into a massive mistake in R. And it has also become the tough task to recover this problem.
In this comparison, SAS is a clear winner. You should not opt for R if you’re a beginner in the programming industry.
Data is growing at a rapid pace. With the evolution of technology and the increasing population, the number of information is also increasing. That’s why today we need to have the best software or programming language that can handle the massive amount of data.
SAS is offering the ability to handle an enormous amount of data with ease.
On the other hand, R is not the best option for handling a massive amount of data. Because R works only on RAM and RAM cannot handle an enormous amount of data. You can use packages of plyr and dplyr for data storing purposes in R., But still, it is not the best option. Another time SAS is better than R.
The world is growing with the best GUI. In terms of data science and data analytics graphics plat a vital role. Graphic help the data scientist and data analyst to visualize and analyze the data. R offers the best GUI. It offers a variety of packages for this job i.e.ggplot, Lattice, and RGIS.
On the other hand, SAS is not a great GUI programming language. But SAS is offering some of the features that improve the GUI of the programming languages. But it is not popularized among the users. So based on graphic R is the winner.
Working with Big Data
Big data is in trend, all because of growing the number of data sources and data quantity. R and Python is the primary language for Big Data. R offers some of the great features to utilize the Big Data, Data Science, and Data Analytics. Whenever we talk about the data, we can’t ignore the R programing language.
R provides the integration with Hadoop (one of the best data warehouses). If you want to perform analytics functions at the scale of Machine Learning capabilities, then go for R. On the other hand, SAS also compatible with Hadoop.
Even it execute analytics with Hadoop without moving the cluster data. But still, SAS is not the best option for Big Data. R is the clear winner of this battle.
The best ever part of the R programming language is, it is an open-source programming language. Therefore anyone can use it without any charges and paid license. It is freely available over the internet. Both the small and medium enterprises use R.
Whenever the business wants to scale the R programming. They can scale the R programming using various libraries and packages. These libraries and packages can be used in any application and functions.
On the other hand, SAS is the best option for large enterprises. SAS is used in end to end infrastructure deployment. It is also used in data warehousing, data quality, and data analytics.
In other words, it provides complete features to the large enterprises to run their operations. On the stage, there is a tie between these two.
R is an open-source programming language. That’s why it is free to use. It is not just free, but it also offers quick updates to the programmers. R also provides the free packages to run the R programming efficiently and with added features.
On the other hand, SAS is quite expensive as compared with R. But, if you want to use SAS, then you need to purchase the license of SAS to use it as a genuine customer. Based on cost, R is a clear winner.
R doesn’t provide the customer support to the programmers. R is not a licensed product. That’s why there are not services support for the customers. It makes it difficult for programmers to tackle the issue with the R programming language.
Because they may not find a quick solution to the problem. But don’t worry R provide the full community support to the programmer. Whenever the programmer faces any difficulty, then they can ask for help within the community.
On the other hand, SAS is a licensed product; thus, it offers full services support to the customers. It also provides community support where customers can ask for help anytime.
Accordingly, all the queries and technical challenges of the customers quickly sorted.
R is an object-oriented programming language. It is written in C and Forton. But you can run it in any operating system and platforms. Along with that it also integrated with other programming languages. Thus it is language-independent.
On the other hand, SAS is based on SQL languages, and it is a procedural language. R is the winner of this comparison.
SAS offers extensive data security to its customers. Most of the MNC uses SAS and rely on it for data security. We all know that the licensed products always offer the best security as compared with the open-source software. Open-Source software still lacks data security. Thus there is no comparison of data security between SAS and R.
The Final Verdict of SAS Vs R
Now we have seen the comparison between SAS Vs R on the basis of some valid points. After comparing them, we have got the idea that SAS and R both have their own set of customers or users. Majority of companies would like to prefer SAS because it is more secure than R.
The company can also hire the best SAS operator who can do the best job with SAS. If we talk about the R, it is still popular among the small and medium enterprises.
These companies would not like to invest a massive amount of data analytics job. Startup companies are using R without having a second opinion. Both of these software are equally popular.
Whether you are doing certification in R or SAS, there is no need to worry because both of them having the job opportunities. Now you can choose the better one between SAS vs R.