SAS Certification Training

Goal: This module introduces you to import datasets and control the import of datasets into SAS and ultimately concatenating them.

Objective:

At the end of this module, you should be able to:

• Bring in your external data into SAS and modifying it.
• Describe and subset permanent datasets.
• Modify/Delete existing columns
• Concatenate Datasets

Topics:

• Import of Data in SAS
• Manipulating influx of datasets into SAS
• Creating a new variable
• Working with Temporary and Permanent Datasets
• Set and Merge Statements

Hands On:

• Demonstrating import of external data within SAS using INFILE
• Demonstrating import of external data within SAS using PROC IMPORT
• Creating Permanent Datasets
• Performing operations with KEEP, DROP and RENAME and LABEL options
• Constructing a new variable
• Creating integrated datasets using SET/MERGE

Goal: This module introduces the concept of looping and its implementation in the SAS programming language. You will explore arrays and functions to simplify complications in SAS programming.

Objective: At the end of this module, you should be able to:

• Demonstrate dependent and independent looping
• Master data step programming with SAS functions
• Simplify processing with SAS Arrays

Topics:

• Conditional& Iterative Processing
• SAS Arrays
• Useful SAS Functions
• PUT/INPUT Functions
• Date/Time Functions
• Numeric Functions
• Character Functions

Hands On:

• Use of DO, DO WHILE, DO UNTIL, IF ELSE, ELSE, ELSE IF
• Demonstrate the use of arrays in SAS
• Operation with INPUT/PUT functions
• Writing a Program with date/time functions
• Performing programming with Numeric functions
• Executing program with Character Functions

Goal: You will learn the analysis of your statistical data with advanced SAS procedures

Objective: At the end of this module, you should be able to:

• Explain Statistical Procedures
• Define priorities to your statistical data
• Discuss statistics associated with a variable
• Express correlation between two or more variables

Topics:

• Proc Dataset
• Proc Format
• Proc Sort
• Proc Means
• Proc Freq
• Proc Surveyselect
• Proc Transpose
• Proc Summary
• Proc Rank
• Proc Corr
• Proc Univariate

Hands On:

• Obtaining statistical means of variables
• Checking the degree of dependence within different variables
• Generating ranks for statistical data
• Performing re-structuring of data
• Conducting sampling: Random and Stratified

Goal: You will learn to model estimate and classify events based on the values of dependent variables. You will be taught to perform different types of clustering methodologies to bunch your observations.

Objective: At the end of this module, you should be able to:

• Define clustering and its types
• Explain clustering algorithms
• Nest data in different clusters
• Analyse the regression between two or multiple variables
• Model and estimate an event based on Logits

Topics:

• Introduction to Clustering
• Hierarchical Clustering
• Non-Hierarchical Clustering (K means Clustering)
• Simple and Multiple Linear Regression
• Logistic Regression

Hands On:

• Demonstrate the use of PROC CLUSTER
• Writing a SAS advanced program with PROC FASTCLUS
• Performing operations on regression with PROC REG
• Demonstrate modelling using PROC LOGISTIC

Goal: You will learn to reduce the degree of complexity of a problem by developing& resolving optimization models and ultimately routing detailed presentation output from SAS in desired formats and destination.

Objective: At the end of this module, you should be able to:

• Discuss data optimization
• Acquire optimized models for complex problems
• Resolve optimization models
• Describe the Output Delivery System in SAS
• Explain the use of ODS statement for creation of different file types

Topics:

• What is Data Optimization?
• Realizing Optimization Models
• Using Proc Optmodel
• Solving the Rosenbrock Problem
• Introduction to ODS
• Benefits of using ODS
• Generating rtf file
• Generating pdf file
• Generating html file
• Generating doc file

Hands On:

• Writing a program with PROC OPTMODEL
• Solving the optimization model using SOLVE
• Extracting optimized outputs
• Routing quality presentation files
• Create html files
• Create rtf file
• Create pdf and doc files

Goal: You will learn to invoke SQL in SAS.

Objective: At the end of this module, you should be able to:

• Write SQL code using various styles of the SELECT statement
• Use CASE/WHEN clauses for conditionally processing the data
• Systemize appearance of observations
• Join data from two or more data sets

Topics:

• Creating new tables
• The SELECT statement
• Sorting Data
• The CASE expression
• Other SELECT statement clauses
• JOINS and UNIONS

Hands On:

• Demonstrating the SQL Procedure
• Writing the SELECT clause
• Application of WHERE clause
• Merging Datasets
• Using ORDER BY clause

Goal: You will explore how to automate a complex repeated process in SAS with the use of Macros.

Objective: At the end of this module, you should be able to:

• Introduction to Macros
• Benefits of using SAS Macros
• Macro Code Constituents
• Macro Variables
• Macro Step
• Positional Parameters to Macros

Topics:

• Introduction to Macros
• Benefits of using SAS Macros
• Macro Code Constituents
• Macro Variables
• Macro Step
• Positional Parameters to Macros

Hands On:

• Demonstrate the use of Macro variables in SAS
• Writing a Macro code to simplify a program
• Demonstrate Macro step programming
• Performing Macro coding by passing parameters

At the end of this course, you should be able to:

• Perceive Analytics with SAS
• Explain SAS GUI, datasets, import/export of manipulated data
• Gain in-depth knowledge of integrating and refining datasets
• Perform conditional and iterative looping into your SAS program
• Simplify a SAS program with SAS arrays
• Analyse statistics and perform advanced statistical techniques with SAS
• Perform automation on complex repeated tasks using MACROS
• Implement and invoke SQL queries in SAS program
• Execute ODS statement with SAS
• Build and solve models using PROC OPTMODEL

• The Edureka SAS training certifies you as an ‘in demand’ SAS professional, to help you grab top paying analytics job titles with hands-on skills and expertise around data mining and management concepts.
• SAS is the primary analytics tool used by some of the largest KPOs, Banks like American Express, Barclays etc., financial services irms like GE Money, KPOs like Genpact, TCS etc., telecom companies like Verizon (USA), consulting companies like Accenture, KPMG etc use the tool effectively.

Anyone who wants to learn programming with SAS can start right away! The course is exclusively designed for students and professionals aspiring to make a career in Data Analytics with SAS.

• SAS Developers
• Analytics Professionals

Other professionals, from technology field, willing to acquire a solid foundation of this widely-used Analytical language, can also opt for this course.

It would be advantageous for you to have prior programming experience and familiarity with basic concepts such as variables, flow-control, and functions along with basic knowledge of Stats. But if you have none and are motivated you will do fine.

For executing the practicals a detailed installation guide is provided in the LMS for setting up the SAS University Edition software environment which has a lifetime validity. In case you come across any doubt, the 24*7 support team will promptly assist you.

Towards end of the course, you will get an opportunity to work on a live case study from the banking domain which happens to be one of the most data intensive industries.

Industry: Banking

Data: Customer-level, Accounts-level and Transaction level

Problem-statement: To build a Customer Analytics Record.

A unique feature of this project is that though it will be mimicked for a bank, it has much wider application across almost all the B2C (and even a few B2B) industries.