Mastering the Basics of SAS Software: Your Gateway to Success

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Are you eager to embark on a journey into the world of SAS software? If you’re a beginner or planning to start learning SAS, then you’ve come to the right place! In this blog post, we will cover all the essential concepts that will not only help you kickstart your SAS programming journey but also ensure that you grasp the fundamentals with a clear understanding.

Introduction

Many students often skip the fundamental concepts and dive straight into creating datasets using the DATA step. As a result, they face difficulties in understanding the terminologies and may even become discouraged early in their SAS learning phase. But fear not, by the end of this article, you will feel well-prepared to grasp the basic SAS concepts and start your SAS programming adventure with confidence.

Commonly Used SAS Environments

Before we dive into the core concepts, let’s briefly explore some of the commonly used SAS environments:

a. SAS 9.4 :

 SAS 9.4 is one of the most widely used versions of the SAS software suite. It offers a comprehensive set of tools for data analysis, reporting, and visualization.


b.  SAS 8.2 Enterprises Guide :

SAS Enterprise Guide provides a user-friendly interface for SAS, making it easier for users to interact with data, create reports, and perform analyses.


c. SAS On Demand :

SAS On Demand offers a cloud-based platform where users can access SAS software and tools via the internet without the need for local installation.


NOTE : No matter which environment you are using all environment provide you all the data handling feature in each environment.

 

1 . SAS Steps

In SAS, a sequence of steps makes
up a SAS program, and it typically starts with two main steps:

a. DATA STEP: 

The DATA step is the core of SAS programming, where datasets are created or modified. It involves reading raw data, manipulating it, and creating new datasets.

b. PROC STEP: 

The PROC step (short for “procedure”) is used to perform various data processing tasks, including statistical analysis, data summarization, and report generation.

To recognize SAS steps, keep in mind that they all end with a semicolon “;”. Let’s take an example to
count how many steps are involved in the following program:

 

 

Data SASNODES.CLASS;

SET SASHELP.CLASS;

Length school_name $ 50.

School_dist $ 25. Comments $ 200.;

School_name=”SAS INSTITUTE”;

School_dist=”MUMBAI”;

Comments=””;

run;

 

The correct answer is 6, counting the number of semicolons.

2 . Step Boundaries

SAS steps are separated by semicolons, but DATA steps have specific boundaries that indicate their end. These boundaries include:

 

  1. RUN : The RUN statement signals the end of the DATA step, indicating that SAS should process the data and create the specified datasets.
  2. QUIT : The QUIT statement is used to signal the end of a PROC step, indicating that SAS should stop processing the procedure.

Let’s expand on the previous example and add an additional PROC step:

DATA SASNODES.CLASS;

SET SASHELP.CLASS;

LENGTH SCHOOL_NAME $ 50.

SCHOOL_DIST $ 25. COMMENTS $ 200.;

SCHOOL_NAME=”SAS INSTITUTE”;

SCHOOL_DIST=”MUMBAI”;

COMMENTS=””;

RUN;

 

PROC MEANS DATA=SASNODES.CLASS;

CLASS AGE;

OUTPUT OUT= AVERAGE;

RUN;

 

PROC SQL;

CREATE TABLE FINAL AS

SELECT * FROM AVERAGE;

 

QUIT;

 

3 . Extensions

Just like other files have their own extensions (e.g., .XLSX, .CSV, .DOCX), SAS datasets and SAS programs have their unique extensions:

  1. SAS Dataset: “.sas7bdat” – SAS datasets are stored in files with the extension “.sas7bdat”. These files contain the actual data in a binary format.
  2. SAS Program: “.sas” – SAS program files have the extension “.sas”. These files contain the SAS code and instructions for data processing and analysis.

4 . SAS Dataset

In SAS, data values are organized in a table format with rows and columns. Each row represents an observation, while each column represents a variable. SAS datasets are the backbone of data manipulation and analysis in SAS.