Tuesday, August 27, 2019

SAS vs R: Which One is Better Statistics Language

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:-


SAS

The statistical analysis system is known as SAS. It is one of the world's important statistical tool. It is used in a large organization why it is called a business analytics tool.

It helps the business in its operations; Similarly, it helps companies in data management services and business intelligence capabilities. I called SAS as one of the best data as it helps the company in getting raw data or information from any material.

Most large enterprises use SAS to perform analysis work on various components of the business. It is a licensee. If you want to use R, you must have basic knowledge of SQL. It is used to output statistical analysis in tables and graphs that are processed from spreadsheets and databases.

The important use of SAS is in financial analysis. It also provides a full range of statistical functions and data analytics also provides the best GUI for application deployment. As I mentioned earlier, it's easy to learn, but compared with R it's quite expensive.


R

R is an open-source programming language. This is a low-level programming language. That is why it is used for research and educational purposes. Get the latest updates at regular intervals.

The R language is specifically designed for statistical operations; That is why all its methods are statistical and graphical. R is still a popular language MNC is using R in your organization. Uber, Google, Facebook are the top users of them.

R also provides the flexibility to communicate with other languages. It is more powerful than the SAS, but mastering the R is quite challenging than the 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

Provide complete statistical flexibility using algorithms and packages in the following.

Ability to collect and analyze social media data.

Use for predictions in data science.

To unravel data from different websites.

Integration with other languages.

Great data view platform.


Features of SAS

Project Management and Operations Research

Report formation with standard graphics

Data updates and revisions

Powerful data handling language

Read and write any data format

Best Data Cleanup Tasks

Ability to interact with multiple host systems
Parameters of Comparison (SAS vs R)


Ease of Learning

SAS is undoubtedly easy to learn a programming language. If you want to learn a new tool without any knowledge or experience with the programming language. Then you should opt for SAS.

The SAS allows us to analyze SQL code, macros integration, and so on. If you have basic knowledge of SQL, you can learn SAS quickly. But if you are a beginner, learning SAS will be a great experience for you.

R is a low-level programming language. That's because it's a little harder to learn R than SAS or any other programming language. If you are going to learn R, you should have a basic knowledge of programming.

It is very difficult to work with a low-level programming language. Because a small problem can turn into a big mistake in R and it has become a difficult task to fix this problem.

In comparison, SAS is a clear winner. If you are getting started in the programming industry, you should not opt for R.


Managing Data

The data is growing at a fast pace. With technology developing and growing population, the number of information is also increasing. That is why today we need the best software or programming language to handle huge amounts of data.

SAS is providing the ability to handle huge amounts of data with ease.
On the other hand, R is not the best option to deal with huge amounts of data. Because R only works on RAM and cannot handle a huge amount of RAM data. You R. You can use the package of plyr and dplyr for the purposes of storing data in, but still, this is not the best option. The second time SAS is better than the R.


Graphics

The world is growing with the best GUI. Data science and data analytics play an important role in graphics. Graphic data helps scientists and data analysts to visualize and analyze data. R offers the best GUI. It offers a variety of packages for this job i.e. ggplot, Lattice, and RGIS.

SAS, on the other hand, is not a great GUI programming language. But SAS is offering some features that improve the GUI of programming languages. But it is not popular among users. So graphic is the winner based on R.


Working with Big Data

Big data is in circulation, due to the increasing number of all data sources and data volume. R and Python are the primary languages for Big Data. Big Data offers some great features for using data science and data analytics. Whenever we talk about data, we cannot ignore the R programming language.

Provides integration with R. Hadoop (one of the best data warehouses). If you want to perform analytics functions on the scale of machine learning capabilities, go to R. On the other hand, the SAS is also compatible with Lado.

It performs analytics with Hadoop even without transferring the cluster data. But still, SAS is not the best option for Big Data. R is the clear winner of this fight.


Industry Deployment

R is the best part of the programming language, it is an open-source programming language. So, one can use it without any fee and paid license. It is easily available on the Internet. Both small and medium enterprises use R.

Whenever the business wants to scale R programming. They can scale R programming using different libraries and packages. These libraries and packages can be used in any application and functions.

On the other hand, SAS is the best choice for large enterprises. SAS is used to eliminate infrastructure deployment. It is also used in data warehousing, data quality, and data analytics.
In other words, it provides full facilities for large enterprises to operate their operations. On stage, there is a tie between the two.


Cost

R is an open-source programming language. So it is free to use. It's not only free, but it also provides quick updates to programmers. R offers free packages to run R programming efficiently and with additional features.

On the other hand, SAS is quite expensive compared with R. But, if you want to use SAS, you need to buy the SAS license to use it as an actual customer. Depending on the cost, R is a clear winner.


Service Support

R does not provide customer support to programmers. R is not a licensed product. That is why there is no support of services for customers. This makes it difficult for programmers to deal with problems with the R programming language.

Because they cannot find a quick solution to the problem. But don't worry R provide full community support to programmers. Whenever programmers face any difficulty, they can ask for help within the community.

SAS, on the other hand, is a licensed product; Thus, it provides full-service support to the customers. It also provides community support where customers can ask for help at any time.
Accordingly, all the queries and technical challenges of the customers were quickly resolved.


Language-Independent

R is an object-oriented programming language. It is written in C and Forton. But you can run it in any operating system and platform. It is also integrated with other programming languages. So, it is language-free.

On the other hand, SAS is based on SQL languages, and it is a procedural language. R is the winner of this comparison.


Data Security

SAS provides comprehensive data protection to its customers. Most MNC uses SAS and depends on it for data security. We all know that licensed products always provide the best protection compared to open-source software. Open-source software still lacks data protection. Thus there is no comparison of data security between SAS and R.


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The Final Verdict of SAS Vs R

Now we have seen the comparison between SAS vs R based on some valid points. After comparing them, we got the idea that both SAS and R have their own set of customers or users. Most companies would prefer to prioritize The SAS as it is more secure than r.

The company can also have the best SAS operator who can do the best work with SAS. If we talk about R, it is still popular among small and medium enterprises.

These companies would not like to do a large amount of data analytics jobs. Startup companies are using R without a second opinion. Both these software are equally popular.

Whether you are getting a certificate in R or SAS, there is no need to worry because both have job opportunities. Now you can choose the better one between SAS Vs R.

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