Advantages | Disadvantages of SAS Programming Language
We have discussed features of the SAS programming language in the previous tutorial. In this tutorial, we will discuss the various advantages and disadvantages of the SAS programming language.
So, let's proceed ....
Advantages of SAS
There are several advantages of SAS Programming Language:
1. Easy to learn
SAS is very easy to learn syntax. It can be learned easily without any programming skill so that anyone can learn it. Coding of SAS is in the form of simple statements. It is like giving instructions to the machine what to do.
2. Ability to handle Large Database
SAS is strongly capable of handling large database very easily.
3. Easy to Debug
SAS is a very comprehensible language. The process of debugging is very easy. It is easy to understand and correct the error that the log window states clearly.
4. Tested Algorithms
The algorithm implemented in the SAS program is fully tested and analyzed by developers. Every version of SAS is tested in a controlled environment, before release. Testing is possible because SAS is a closed source language.
5. SAS Customer Support
The features of SAS are given below:
6. Data Security
In the extension of the above point, the data in SAS is completely secure. In the case of office use, without license we cannot extract data. Manipulation is not possible because of Data security, and this is the reason behind its popularity in the corporate world.
Company's data is confidential here that's why it is a close source of company
SAS software is a primary tool for many large scale companies. Company's data is confidential here that's why it is a close source of company.
SAS is preferred over R and any other language used for analysis. R is open source; therefore, data security is not guaranteed. Only freelancer uses the R.
7. SAS GUI
SAS is a language that has made statistical computing easier for non-programming users. It has an amazing GUI (Graphical User Interface). Its user interface has various tools like plots, graphs, and highly versatile libraries.
SAS has developed for a long time. It provides a well formatted and absolutely correct output, which is easy to understand.
9. Huge Job Prospects
Due to the fact that SAS has been used in the industry for a very long time, there are huge employment potentials. Professionals learn SAS as a condition so that they can enter in the analytics industry. The person who commands the SAS can easily learn R and Python. This is a market leader in the Analytics industry.
Disadvantages of SAS
Below are some of the major disadvantages of SAS Programming:
The cost of SAS software is one of its major disadvantages. We cannot use all its functions without a license, which is very expensive.It is a complete software due to being in a closed environment, so there is no facility for the license of any single function that we need. All these prerequisite makes it very expensive.
2. SAS is Not Open Source
R is always quicker than SAS in implementing an algorithm related to machine learning. The reason behind this, R is an open source so that anyone can operate it, but this is unfavorable for SAS. SAS is a closed environment software, and it doesn't support open source so, the algorithm of SAS procedures is not for the use of public. SAS is available only in the licensed version. Algorithms are not openly available for public research.
3. Lack of Graphic Representation
There is more availability of R for advanced graphics. Its graphics presentation is much more vivid and consistent than SAS. It has a more descriptive plot, diagram, and graph.
4. Difficult Text Mining
Text mining in R is free, but in SAS, it uses SAS Enterprise. Text mining means extracting information from text. This is to decrypt a written code. It tells us what the written text can decide in terms of decision making. This is the process in which the text converts data into decision making and analysis.
5. Difficult than R
SAS is more procedural language than R. There are more lines of code than R. We can quickly apply new innovations such as statistical learning and machine learning in R in comparison to SAS. Many packages which are free in R, are chargeable in SAS. For example, Text Mining, Time Series Forecasting (SAS / ETS), etc.
Since there are various advantages and disadvantages of SAS Programming. But in the Field of analytics, SAS has its own popularity among other languages. It has a wide job market, more security than any other language and a close source language. SAS has a protected environment for developers to test algorithms. It is always bug-free and has very helpful customer support.