Uses, Advantages and Disadvantages of SAS

What is SAS Language?

The SAS language may be a programing language used for applied mathematics analysis, created by Anthony James Barr at North geographic area State University.

It will scan in knowledge from common spreadsheets and databases and output the results of applied mathematics analyses in tables, graphs, and as RTF, markup language and PDF documents.

The SAS language runs beneath compilers which will be used on Microsoft Windows, Linux, and varied alternative operating system and mainframe computers.

The SAS System and World Programming System (WPS) ar SAS language compilers.

Uses of SAS

You can use SAS software through both a graphical interface and the SAS programming language, or Base SAS.

With SAS software, you can

  • access data in almost any format, including SAS tables, Microsoft Excel tables, and database files.
  • manage and manipulate your existing data to get the data that you need. For example, you can subset your data, combine it with other data, and create new columns.
  • analyze your data using statistical techniques ranging from descriptive measures like correlations to logistic regression and mixed models to sophisticated methods such as modern model selection and Bayesian hierarchical models.
  • present the results of your analyses in a meaningful report that you can share with others. The reports that you create can be saved in a wide variety of formats, including HTML, PDF, and RTF.

Advantages and Disadvantages of SAS

Advantages

Advantages of SAS

i. Simple to learn

SAS helps to easily find out the syntax. It is learned simply by one with none programming skills, committal to writing is in sort of straightforward statements. It’s like instructing a machine what to try to.

ii. Ability to handle giant information

SAS contains a robust ability to handle giant information terribly simply.

iii. Simple to correct

SAS may be a terribly fathomable language. It is simply debugged. Its log window clearly states the error which may be understood and corrected.

iv. Tested algorithms

The rule enforced within the SAS program is totally tested and analyzed. Each version of SAS is 1st tested in an exceedingly controlled atmosphere, before free.

This can be potential as a result of SAS may be a closed language.

v. SAS client support

SAS happiness to a corporation has correct observance. It’s sort of a complete organization. it’s terribly spontaneous client support.

As SAS may be a closed supply tool, it will solely be altered by the SAS organization. No external adulteration is feasible. All issues are handled by SAS client support.

vi. Knowledge Security

Extending the on top of purpose, knowledge in SAS is totally secured. It cannot be extracted, just in case of workplace use while not a license. knowledge security prevents it from manipulation.

And this can be one reason for its quality within the company world. SAS is employed as a primary tool by several massive firms. Being an in-depth supply, a company’s knowledge is confidential here.

R is employed principally by freelancers. its open supply thus knowledge security isn’t secure. SAS is most popular professionally over the other language used for analysis.

vii. SAS GUI

SAS is one such language that has created applied math computing easier for non-programming users. It’s an incredible Graphical program (GUI). Its numerous tools like graphs, plots, and an extremely versatile library are useful.

viii. Nice Output

SAS has evolved over an extended amount of your time. It’s nice formatted output, one that is well fathomable.

ix. Large Job Prospects

This is a reality SAS being employed from an awfully very long time within the trade, contains a large job prospect.

Professionals learn SAS as a necessity to enter the analytics trade. One United Nations agency commands SAS will learn R and Python simply. it’s the market leader within the analytics trade.

Disadvantages

Disadvantages of SAS

i. Cost

One major disadvantage of SAS is the cost. Being in a closed environment, it a complete software in itself. A person cannot use it all applications without a proper license.

ii. SAS is not open source

R has always implemented new algorithm related to machine learning more quickly than SAS. The main reason is R can be operated by anyone as it is open source, but this not true for SAS.

SAS works in a closed environment. So, the algorithms used in SAS procedures are not made public for common use. They are available in licensed version. They are not available openly for public research.

iii. Lack of graphic representation

R has a greater availability for advanced graphics. Its graphics presentation is far more vivid and compatible than SAS. It has more descriptive plots, graphs, and diagrams.

iv. Difficult Text Mining

Text mining is free in R, but in SAS, it uses SAS enterprise.

Text mining means extracting information from text. It’s like deciphering a written code.

It tells you what the written text can infer in terms of decision making. It is the process in which text convert to data for decision making and analysis.

v. Difficult than R

SAS is more of a procedural language in comparison to R. It has more lines of codes than R.

New innovations like statistical learning and machine learning are more quickly applied in R than in SAS.

Many packages that are free in R are chargeable in SAS. For example, Time series forecasting (SAS/ETS), Text mining etc.

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