SAS Training & SAS Certification in Chennai

1. Base SAS


2. Advance SAS


3. Clinical SAS Programming


4. Predictive Modeling


5. Clinical Data Manager


6. Platform Administrator


7. SAS Data Integration Studio


8. BA Data Mining with Statistics


9. Business Intelligence


10. Data Management and Reporting

Base SAS Training

The Program will cover three modules

1 . SAS Programming I Essential

• Navigate the SAS windowing environment
• Read various types of data into SAS dat a sets
• Validate and clean SAS data sets
• Create SAS variables and s ubset data
• Combine SAS data sets
• Create and en hance listing and summar y reports

2 . SAS Programming II: Manipulation Data with DATA step

• Control SAS data set input and output
• Combine SAS data sets
• Summarize, read, and write different ty pes of data
• Perform DO lo op and SAS array processing
• Transform character, numeric, and date variables

3 .SAS Base Programming Exam for SAS 9.3

• Read, create, and combine SAS data sets
• Read and create raw data files
• Create variabl es using the a ssignment statement and using conditional process ing
• Manipulate da te using SAS functions
• Process data w ith DO loops and with ar rays
• Create differe t types of re ports using th e PRINT procedure, the REPORT procedure, the FR EQ procedure, or the MEANS procedure
• Create formats with the FORMAT procedure
• Create HTML reports with ODS

Advanced SAS Training in Chennai

INTEGRATED COURSE OUTLINE

The Program will cover three modules

1 . SAS Macro Language

This course focuses on the components of the SAS macro facility and how to design, write, and debug macro systems. Emphasis is placed on understanding how programs with macro code are processed.

• Perform text substitution in SAS code
• Automate and customize t he production of SAScode
• Conditionally or iteratively construct SAS code
• Use macro variables and macro functions



2 . SQL Processing with SAS

How to process SAS data using Structured Query Language (SQL)- SAS Advanced Programming Exam for SAS 9.3.

• Query and sub set data
• Summarize and present dat a
• Combine tables, including complex joins and merges
• Create and mo dify table vie ws and indexes
• Replace multi ple DATA and PROC steps with one SQ L query



3 . SAS Programming III: Advance Techniques & efficiency

SAS Advanced Programming Exam for SAS 9.3.

• Control memory, I/O, and CPU resources
• Create and use indexes
• Combine data horizontally and vertically
• Use hash and hiter DATA step component objects, arrays, and for mats as looku p tables
• Compress SAS data sets
• Sample your SAS data sets



Clinical SAS Training In Chennai

Clinical SAS Training Course Content

In this program the participants will learn how to

Base SAS

• SAS programming 1: Essentials
• SAS programming II: Data manipulation techniques
• Base SAS Certification Review



SAS/SQL

SAS PheedIT General Introduction

Overview/introduction to PheedIt including Roles and Online Documentation + Demo

PheedIt Administration

• Library Administration, Librarian Role + Demo
• Workshop for Library Administration
• Study Setup Study, Definer Role + Demo
• Workshop for Study Definer Role, start
• Workshop for Study Definer Role



Data Entry

• Workshop for Data Entry
• Discrepancy Management, Disc. Manager Role + Demo
• Workshop for CDM Role
• Investigator Role, Monitor Role
• Clinical Data Manager (CDM) Role +Demo
• Statistician Role + Demo
• Dictionary Coding
• Workshop CDM



Clinical SAS Data Integration

• Register source data and target tables
• Create jobs and explore the functionality of the Job Editor
• Work with many of the various transformations
• Enhance table relationships using integrity constraints, key, and indexes
• Work with slowly changing dimensions
• Create custom transformation with the Transformation Generation Wizard
• Document and deploy jobs
• Administer SAS Data Integration Studio



SAS/Report

SAS/Access




SAS Predictive Modeling Training in Chennai

SAS Predictive Modeling Course Content

Applied Analytics using SAS Enterprise Miner 5.3 (IND1Z)

• Introduction
• Accessing and Assaying Prepared Data
• Introduction to Predictive Modeling with Decision Trees Introduction to Predictive Modeling with Regressions
• Introduction to Predictive Modeling with Neural Networks and Other Modeling Tools Model Assessment
• Model Implementation Introduction to Pattern Discovery Special Topics (Self-Study)
• Case Studies (Self-Study)



Enterprise Guide: ANOVA Regression and Logistic Regression (IND83)

• Introduction to Statistics
• Inferences for the Mean
• Analysis of Variance
• Regression
• Regression Diagnostics
• Categorical Data Analysis



Business Analytics Boot Camp

Integrated Course Outline

Base SAS

• Navigate the SAS windowing environment
• Read various types of data into SAS data sets
• Validate and clean SAS data sets
• Create SAS variables and subset data
• Combine SAS data sets
• Create and enhance listing and summary reports
• Control SAS data set input and output
• Combine SAS data sets
• Summarize,read,and write different types of data
• Perform DO loop and SAS array processing
• Transfrom character,numeric and data variables



Creating Business Intelligence using SAS Reports

• Use several of the business user applications in the platform for SAS Business Analytics
• Create and Exploit dynamic value selection
• Bulid advanced information maps using SAS information Map Studio
• Create advanced SAS BI Dashboard applications
• Produce advanced stored processes able to create dynamic data sources
• Bulid schedule and distribute advanced reports
• Consolidate information into a business reporting application
• Describe the online analytical processing capabilities available in the SAS platform
• Explore the basic functionality of the SAS integration with JMP
• Examine the types of metadata created in the SAS platform



SAS Data integration

• Register soure data and target tables
• Create jobs and explore the functionality of the job editor
• Work with many of the various transformations
• Enhance table relationships using integrity constraints keys and indexes
• Work with slowly changing dimensions
• Create custom transformation with the Transformation Generation Wizard
• Document and deploy jobs
• Administer SAS Data Integration Studio



PLATFORM ADMINISTRATOR

COURSE OVERVIEW

"Reviewing the Platform for SAS Business Analytics"

• Exploring the platform for SAS
• Business Analytics overview
• Exploring the client tier, middle tier, server tier, and data tier



Administering the SAS Environment

• Overview of administration tasks



Determining the State of the SAS Environment

• Checking the state of SAS servers
• Exploring the metadata server and repositories
• Troubleshooting the metadata server



Monitoring, Logging, and Troubleshooting SAS Servers

• Identifying different types of SAS servers
• Monitoring SAS servers and spawners
• Logging SAS servers and spawners
• Troubleshooting SAS servers



Backing Up the SAS Environment

• Backing up metadata with the Backup Wizard
• Exploring OMABAKUP
• Scheduling backups
• Backing up physical files



Administering Client Applications

• Exploring connection profiles
• Using roles to control access to application
• Functionality
• Exploring SAS folders



Administering Users

• Defining regular users and groups
• Defining administrative users
• Giving users access to servers



Administering Data Access

• Registering libraries
• Tables in the metadata
• Updating table metadata
• Pre-assigning libraries
• Troubleshooting data access



Securing Metadata

• Introduction to metadata security
• Exploring metadata permission
• Exploring predefined ACTs
• Securing content in the folder tree
• Securing content outside the folder tree
• Creating additional ACTs



Moving Metadata

• Replicating an entire repository
• Promoting selected content



Updating the SAS Environment

• Applying hot fixes to the SAS environment



Data manager Boot Camp Course Content :

Integrated Course Outline

Base SAS

• Navigate the SAS windowing envionment
• Read various types of data into SAS data sets
• Validate and clean SAS data sets
• Create SAS variables and subset data
• Combine SAS data sets
• Create and enhance listing and summaty reports
• Control SAS data input and ouput
• Combine SAS data sets
• Summarize, read,and write different types of data
• Perform DO loop and SAS array processing
• Transform character, numeric and data variables



Advance SAS

• Create a framework for developing macro application
• Develop reusable macros
• Read and process data
• Pass and process data
• Query and subset data
• Summarize and present data
• Combine tables, including complex joins and merges
• Create and modify tables views and indexes
• Replace multiple DATA and PROC steps with one SQL query
• Control memory,I/O, and CPU resources
• Create and use indexes
• Combine data horizontally and vertically
• Use hash and hiter DATA step component objects, arrays, and formats as tookup tables
• Compress SAS data sets
• Sample your SAS data sets



Clinical SAS programming Course Content

Overview Of Course

• Basic of SAS Programming
• Introduction to the pharmaceutical industry & clinical Reserch
• Introduction to clinical Reserch Organization
• Familiarize with frequently used clinical trial terminology
• Advance SAS
• Clinical SAS
• Introduction with Clinical study Documents
• Regulatory Authorities & Application Process (USFDA,EU,ICH)
• Clinical SAS Data Integration
• Creation of Clinical Datasets (DM, AE, MH, VS, and PE etc)
• Basics of Analysis Datasets
• Compliance, Auditing & Quality Control in Clinical Research
• Project on clinicl Trial Dummy Data



Boot Camp for SAS Business Intelligence Developer

Integrated Course Outline

Base SAS

• Navigate the SAS windowing environment
• Read various types of data into SAS data sets
• Validate and clean SAS data sets
• Create SAS variables and subset data
• Combine SAS data sets
• Create and enhance listing and summary reports
• Control SAS data set input and output
• Combine SAS data sets
• Summarize read and write different types of data
• Perform DO loop and SAS array processing
• Transform character numeric and date variables



Creating Business Intelligence using SAS Reports

• Use several of the business user applications in the platform for SAS Business Analytics
• Create and Exploit dynamic value selection
• Bulid advanced information maps using SAS Information Map Studio
• Create advanced SAS BI Dashboard applications
• Produce advanced stored processes able to create dynamic data sources
• Bulid Schedule and distribute advanced reports
• Consolidate information into a business reporting application
• Describe the online analytical processing capabilities available in the SAS platform
• Explore the basic functionality of the SAS integration with JMP
• Examine the types of metadata created in the SAS platform



Creating Business Intelligence for your Orgainzation

Integrated Course Outline

Introduction

• Exploring the paltform for SAS Business Analytics
• introducing the course environment and scenario



Introducing the Business User Reporting Applications

• Defining the business user role and reporting applications
• Exploring the SAS Add In for Microsoft Office
• Exploring the SAS Web Report Studio
• Defining the interaction between the business user and the business analyst



Introducing Advanced Reporting Techniques and Roles

• Defining the business analyst role and applications
• Modifying an existing information map
• Creating a new SAS BI Dashboard indicator
• Creating data sources for reporting and analysis
• Defining the interaction between the business analyst and the paltform administrator
• Understanding SAS Data Integration capabilities



Creating an Information Map

• Understanding SAS Information Maps
• utilizing different data sources
• Exploiting dynamic subsetting of data
• Creating prefilters to subset the information map
• Using the Information Map LIBNAME Engine
• Creating information maps programmatically self-study



Building a SAS BI Dashboard Application

• Understanding SAS BI Dashboard
• Building the SAS BI Dashboard components
• Building advanced SAS BI Dashboard components



Building Stored Processes

• Understanding SAS Stored Process concepts
• Creating a stored process from a SAS Enterprise Guide project
• Creating a stored process from a SAS program
• Creating stored process parameters
• Creating a stored process to provide a dynamic data source



Utilizing Advanced Techniques with SAS Reports

• Building advanced reports with SAS Web Report Studio
• Creating and using SAS report templates
• Linking reports in SAS Web Report Studio
• Scheduling and distributing SAS Reports
• Building SAS Reports with SAS Enterprise Guide
• Creating Shared Prompts



Consolidating Information into a Business Reporting Application

• Creating the business reporting application



Introducing Multidimensional Data Sources

• Understanding online analytical processing concepts
• Building an OLAP cube with SAS OLAP Cube Studio
• Building an information map from a SAS OLAP cube



Introducing SAS Visual BI

• Introduction to SAS Visual BI
• Exploring the SAS integration with JMP



Examining the Environment Metadata

• Reviewing the platform for SAS Business Analytics
• Reviewing the course environment



Data Integration Table Course content

Integrated Course Outline

Base SAS

• Navigate the SAS windowing environment
• Read various types of data into SAS data sets
• validate and clean SAS data sets
• Create SAS variables and subsets data
• Control SAS data set input and output
• Summarize , read, and write different types of data
• perform DO loop and SAS array processing
• Transform character, numeric , and data variables



Advance SAS

• Create a framework for developing macro application
• Develop reusable macros
• Read and process macro parameters
• Pass and process macro paramters
• Query and subset data
• Summarize and present data
• Combine tables, including complex joins and merges
• Create and modify table views and indexes
• Replace multiple DATA and PROC steps with SQL query
• Control memory , I/O, and CPU resources
• Create and use indexes
• Combine data horizontally and vertically
• Use hash and hiter DATA step component objects, arrays , and formats as lookup tables
• Compress SAS data sets
• Sample your SAS data sets



SAS Data Integration

• Register source data and target tables
• Create jobs and explore the functionality of the job Editor
• Work with many of the various transformations
• Enhance table relationships using integrity constrains, key, and indexes
• work with slowly changing dimensions
• Create custom transformation with the Transformation Generation Wizard
• Document and deploy jobs
• Administer SAS Data integration Studio



Data Mining with Statistics

Integrated Course Outline

Base SAS

• Navigate the SAS windowing environment
• Read various types of data into SAS data sets
• Validate and clean SAS data sets
• Create SAS variables and subset data
• Combine SAS data sets
• Crete and enhance listing and summary reports
• Control SAS data set input and output
• Combine SAS data sets
• Summarize,read,and write different types of data
• Perform DO loop and SAS array processing
• Transform character , numeric,and date variables



Creating Business Intelligence using SAS Reports

• Use several of the business user applications in the platform for SAS Business Analytics
• Create and Exploit dynamic value selection
• Build advanced information maps using SAS Information Map Studio
• Create advanced SAS BI Dashboard applications
• Produce advanced stored processes able to create dynamic data sources
• Build,schedule,and distribute advanced reports
• Consolidate information into a business reporting application
• Describe the online analytical processing capabilities available in the SAS platform
• Explore the basic functionality of the SAS integration with JMP
• Examine the types of metadata created in the SAS platform



SAS Analytics (SAS Enterprise Guide :ANOVA Regression & Logistic Regression , Applied Analytics using SAS Enterprise Miner)

• Generate descriptives statistics and explore data with graphs
• Perform analysis of variance
• Perform linear regression and assess the assumptions
• Use diagnostic statistics to identify potential outliers in multiple regression
• Use chi-square statistics to detect associations among categorical variables
• Fit a multiple logistics regression mode
• Define a SAS Enterprise Miner project and explore data graphically
• Modify data for better analysis results
• Build and understand predictive models such as decision trees and regression models
• Compare and explain complex models
• Generate and use score code
• Apply association and sequence discovery to transaction data
• Use other modeling tools such as rule induction ,gradient boosting ,and support vector machines



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