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SAS programming Certification Training

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Rated 4.7 out of 5

Learners : 1080

Duration :  25 Days

About Course

🌐 SAS Programming Online Training – Course Overview

The SAS Programming Online Training course is designed to help learners gain a strong foundation in data analysis, statistical modeling, and business analytics using (Statistical Analysis System) software. This training covers both Base and Advanced  concepts, including data manipulation, macro programming, and report generation.

Through hands-on sessions, learners will work with real-world datasets, mastering how to import, clean, transform, and analyze data efficiently. The course also focuses on statistical procedures, data visualization, and automation using macros, preparing you for certification exams and data-driven career roles.

This course is ideal for Data Analysts, Programmers, Statisticians, and Business Intelligence Professionals aiming to advance their careers in data analytics and statistical programming.

💡 Key Skills You’ll Learn

  • Environment and Data Step Processing
  • Data Import, Export, and Transformation
  • Merging and Combining Datasets
  • Statistical Analysis using PROC Steps
  • Creating Reports, Charts, and Graphs
  • Macro Programming and Automation
  • Debugging and Performance Optimization
  • SQL Procedures 

🎓 Certification Tracks

  • Certified Base Programmer
  • Certified Advanced Programmer
  • Certified Data Analyst (Viswa Online Trainings)

SAS programming Training Course Syllabus

EXPOSURE IN ORGANISATIONS
  • History
  • comes in ERP sector or not? Why?
  • What is Clinical Research Study?
  • What is SOP (Standard Operating Procedure)?
  • What is DBMS?
  • What is SAP (Statistical Analysis Plan)?
GETTING STARTED WITH SYSTEMS:
  • Managing windows in window environment
  • Why using the S-A-S in different sectors.
  • How to use the data step to read and manipulate complex forms of data
  • Write Data and Proc steps.
  • Data step compile and execution
  • Read any type of external raw data
  • Reading raw data Environment into DATA SET using Input statement & advance INLIFE statement options
  • Working with Data Storage in SAS libraries creation for user-defined libraries and multi-engine architecture
  • Reading data from data set to another data set.
  • To manage the SAS window environment used with global options.
  • To manage existing data with controlling statements and expressions
  • Creating Summary Information, SAS Functions, Transforming Data
  • Changing variable types using the PUT and INPUT functions summarizing data files
  • To expert data from data sets to delimiter files using with data set block
  • Understand error messages in the Log and debug your program
PERFORM ITERATIVE PROCESSING ON DATA:
  • Using Do loops for repetitive calculations and processing
  • Using Arrays to process across observations and processing
UTILITIES TO MANAGE AND WORK WITH DATASETS:
  • Using the update statement to update data in the existing dataset.
  • Using the MODIFY statements to update and modify data in place Merging concepts
  • Concatenation concept in merging
  • Interleaving concepts and merging
  • Different kinds of match merging using MERGE statement using the contribution (IN=) option in merge concept
  • Using ODS concept to generate reports
  • Role of ODS concepts in reporting SAS output
  • To generate output in different panels like RTF, HTML,PDF and XML Using ODS
RELEVANT BASE SAS PROCEDURES:
  • UTILITY PROCEDURES:
  • IMPORT PROCEDURE
  • EXPORT PROCEDURE
  • DB LOAD PROCEDURE
  • COPY PROCEDURE
  • CPORT PROCEDURE
  • COMFORT PROCEDURE
  • DELETE PROCEDURE
  • SETTING PROCEDURE
  • OPTIONS PROCEDURE
  • TEMPLATE PROCEDURE
  • APPEND PROCEDURE
  • COMPARE PROCEDURE
  • SORT PROCEDURE
  • DATASETS PROCEDURE
  • PRINT TO PROCEDURE
  • FORMAT PROCEDURE
  • TRANSPOSE PROCEDURE
  • ACCESS PROCEDURE
  • REPORTING PROCEDURES:
  • PRINT PROCEDURE
  • TABULATE PROCEDURE
  • REPORT PROCEDURE
  • CHART PROCEDURE
  • HART PROCEDURE
  • PLOT PROCEDURE
  • GPLOT PROCEDURE
  •  STAT PROCEDURES:
  • MEANS PROCEDURE
  • SUMMARY PROCEDURE
  • UNIVARIATE PROCEDURE
  • CORR PROCEDURE
  • FREQ PROCEDURE
  • TEST PROCEDURE
  • FREQ PROCEDURE
  • RANK
  • TEST PROCEDURE
  • ANOVA PROCEDURE
  • REG PROCEDURE
  • GLM PROCEDURE
How to use PROC SQL to retrieve INFORMATION from their Data
  • Introduction to SQL Concepts
  • Create new tables, indexes, views, and reports
Joining Data
  • What are Cartesian Products, what is join
  • Inner, FULL, OUTER, LEFT, and RIGHT Joins
  • Union join, Cross joins
  • Set Operator us such as union and intersection joining multiple tables
ADVANCED SQL Topics
  • HOW TO USE SAS MACROS IN SQL
  • How to retrieve Raw data different from DATABASES to SAS environment using SQL Statements
  • To create tables in different databases using SAS SQL statement
  • To manage in different databases using SAS SQL Statements
PASS TROUGH FACILITY
  • Uses of pass-through facility
  • How to communicate with other databases like Access, Oracle, DB2
  • To control and manage other databases from SAS
MACROS
  • Macro Concepts & Advantages
  • Macro Language
  • Macros And Macro Variables
  • Creating Macro Variables & Using Macro Variables
  • Creating Modular Code With Macros
  • Invoking A Macro
  • Adding Parameters to Macros
  • Writing Macros With Conditional Logic
  • Using Various Procedures in Macro Variables
  • Nesting of Macros
  • Multiple And Multi-Level Macros
  • Macro Functions
SAS programming Course Key Features

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SAS programming Online Training FAQ'S

What is SAS used for?
  • SAS is used for data management, statistical analysis, predictive modeling, and business intelligence reporting.

What are DATA and PROC steps in SAS?
  • The DATA step is used for data manipulation, while the PROC step performs analysis and generates reports.

What is a SAS Macro?
  • A SAS Macro automates repetitive code and improves efficiency by dynamically generating SAS statements.

How do you handle missing values in SAS?
  • Missing values can be handled using conditional statements, PROC MEANS, or data cleaning functions.

What is the difference between KEEP and DROP statements?
  • KEEP retains specified variables in a dataset, while DROP removes them during data processing.

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