Courses / Learn Statistical Analytical Software (SAS)

Learn Statistical Analytical Software (SAS)

30 LIVE interactive classes+ 5 Online Tests+ Expert Instructor

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Course Highlights

  • 30 LIVE online classes to learn Statistical Analytical Software
  • Key benefit: SAS meets data analysis needs of the entire organization
  • Course instructor has completed successful groups of SAS teaching

About the Course

Language of Instruction: English, Telugu

Course Description


The SAS System or Statistical Analytical Software is an integrated suite of software for enterprise-wide information delivery. The functionality of the system is built around the four data-driven tasks common to virtually any application : data access, data management, data analysis and data presentation. From traditional statistical analysis of variance and predictive modeling to precise methods and statistical visualization techniques, SAS is designed for both specialized and enterprise wide analytical needs. It provides a comprehensive set of tools that can meet the data analysis needs of the entire organization. Applications of the SAS System include Executive Information Systems, Report Writing and Graphics, Statistical and Mathematical Analysis, Operations Research and Project Management and Statistical Quality Improvement. SAS is used in Banking, Credit Unions, Lenders, Capital Markets, Communications, Education, Higher Education, K-12, Defense, Federal Government, Health and Social Services, Justice and Public Safety, State and Local Government, Health Care Providers, Insurance, Property and Casualty, Life Sciences, Pharmaceuticals Manufacturing, Aerospace, Automotive, Consumer Packaged Goods, Retail, Apparel/Fashion, E-Commerce, General Merchandise, Grocery, Casinos, Computer Services, Freight, Hotels, Software Publishing, Sports, Travel, Utilities Energy and Oil and Gas.


This course will provide you with a thorough introduction to Statistical Analytical Software. Right from the History of SAS to Getting Started with SAS Systems to performing iterative processing to data storage methods and compression to indexing techniques to managing datasets to PROC SQL to Macros to Debugging SAS Programs to Data Warehousing, all topics will be covered. You will learn using a LIVE Virtual Classroom and experience the software first hand. In addition, you will also have access to the class recordings to review what has been discussed.


What’s included in the course:


  • 30 LIVE interactive online classes + Access to class recordings
  • Online access to study material
  • 5 online tests to review your performance


About the instructor:


Meka Raviteja has been teaching SAS to students for last 5 months. He has done B. Pharmacy and is trained in SAS. Through his interactive classes, he has successfully trained students from diverse cultures, nationalities and educational backgrounds. His flexible teaching techniques are arranged according to the needs of individual students. He lives in Andhra Pradesh, India.


Course outline:


History of SAS:


  • SAS comes in ERP sector or not? Why?
  • Role of Statistical Analysis in Clinical Research Study and
  • Banking analysis
  • SAS role in Clinical Research Study and Banking analysis
  • Project Management in Clinical Research Study analysis and
  • Banking analysis
  • What is Clinical Research Study?
  • What is Protocol and role of Protocol in Clinical Research study
  • What is randomization and non randomization?
  • Which is playing main role in Clinical Research Study?
  • What is SOP (Standard Operating Procedure)?
  • What is DBMS?
  • Role of DBMS team in Clinical Research Study
  • What is CDM (Clinical Data Management)?
  • Importance of CDM systems for data loading
  • What is SAP (Statistical Analysis Plan)?
  • Role of SAP in Clinical Research Study
  • SAS Work Flow in Clinical Research Study
  • Relation between SAS and DBMS
  • Interaction between SAS with CDMs for data access
  • Various report generation in Clinical Research Study


Getting started with SAS Systems:


  • Basic operating system commands, operating system file structures
  • Managing windows in SAS window environment
  • Use of different kind of SAS products and how to use in SAS application
  • Difference between the SAS products
  • Why using the SAS 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
  • To run SAS application on different modes
  • Reading internal reading and printing l raw data into SAS
  • Read any type of external raw data into SAS
  • Reading raw data SAS 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
  • Using a single libref to reference some or all SAS libraries reading and printing mixed records formats.
  • Reading packed and zoned decimal data working with EBCDIC and ASCII data
  • Reading data from data set to another data set.
  • To manage the SAS window environment used with global options.
  • Reducing memory requirements with BUFFNO and BUFSIZE working with SAS data set 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
  • Generation data sets to create historical information SAS
  • To expert data from data sets to delimiter files using with data set block
  • Understand error messages in the SAS Log and debug your program
  • Use with Error Handling concepts


Perform iterative processing on data:


  • Using Do loops for repetitive calculations and processing
  • Using Arrays to process across an observations and processing
  • Using DO WHILE and DO UNTIL statements for conditional looping


Data storage methods and compression:


  • SAS Engines
  • Space reduction
  • Data set compression


Indexing techniques and uses:


  • When to use indexes
  • Creating and deleting indexes
  • Index advantages and disadvantages


Utilities to manage and use datasets:


  • Data using append procedure to add date values in existing dataset
  • Using the update statement to update data in existing dataset.
  • Using the MODIFY statements to update and modify data in place
  • Merging concepts
  • Data transformation
  • Concatenation concept in merging
  • Interleaving concept and merging
  • Different kind of match merging using MERGE statement using the contribution (IN=) option in merge concept
  • Using ODS concept to generate reports


Relevant Base SAS Procedures:


  • Organize and sort SAS data sets and working with duplicates
  • To generate listing output use print
  • Comparing data sets with proc compare
  • To create user defined informat and format statements use format
  • Using proc copy to copy data sets
  • Importance of contents procedure
  • Reading data from dataset for reporting use report
  • Using Proc Datasets to modify data set structure , attributes
  • How to use permanent formats , Setting up Integrity Constraints to maintain clean data and Setting up indexes
  • Role of ODS concepts to reporting SAS output
  • To generate SAS output in different panels like RTF, HTML,PDF and XML Using ODS
  • How to use PROC SQL to retrieve INFORMATION from their Data
  • Introduction to SQL Concepts
  • The origin of SQL and why we use it.
  • Create new tables, indexes , views and reports
  • Simple Queries
  • Understanding to SQL Concepts
  • How to specify columns and subset rows
  • Using functions to summarize and group data
  • Ordering data and formatting out
  • Performing group analysis, remerging and sub queries
  • Joining Data
  • What are Cartesian Products , what is join?
  • Inner, FULL, OUTER, LEFT and RIGHT Joins
  • Set Operator us such as union and intersection joining multiple tables


PROC SQL as compared to the data step:


  • Creating Indexes and table in SQL
  • Why we use Views in SQL
  • Performance and space ISSUES
  • How dictionary table and views can simplify programming SQL Options
  • How to retrieve Raw data different from DATABASES to SAS
  • Environment using SQL Statements
  • To create table in different databases using SAS sql statement
  • To manage in different databases using SAS Sql Statements


Pass through Facility:


  • Uses of pass through facility
  • How to communicate with other database like Access , Oracle, DB2
  • To cantrol and manage other databases fro the SAS.
  • To access required data from other databases
  • To create DATAWAREHOUSING environment
  • Basic Statistical Procedures (SAS/STAT) and reporting Procedure
  • To summary statistical Analysis Summary Procedure
  • Producing Statistical with means Procedure
  • Testing Categorical Data with FREQ PROCEDURE
  • Reporting areas in SAS
  • To generate report use with Proc Report
  • Examining Data with Univarate Procedure
  • T-tests and non parametric Comparison
  • Proc ANOVA for one way ANOVA for one way Analysis of Variance
  • Examining Correlations with PROC CORR
  • PROC REG for Regression Analysis
  • Creating bar & PIE Charts
  • Producing BAR & pie chart
  • Enhancing O/P with Title FOOTNOTES Color & font
  • Producing & Overlaying lots
  • CONTROLLING Appearance of axe’s
  • Generating Graphs use with ODS
  • How to work with SAS/ACCESS & SAS /Connect
  • To import data from different PC files use import procedure
  • To export data from different source use access procedure
  • To export data from datasets to different PC files use export procedures
  • Uses of DBLoad procedure and how to work
  • To transport datasets one environment to another environment and
  • One version to another version to another version (windows to UNIX)use with cprot and cimport procedures
  • How to use Upload Procedure
  • How to use Download Procedure


How to work with Macro Language : Introduction to Macros :


  • How the SAS macros Language Works
  • What is the role of macro in SAS
  • Introduction to tokening , compiling and executing a SAS program
  • How the macro Processor Works
  • Applying automatic macro variables
  • Designing customized macro variables
  • Submitting the macro variables in SAS Programming
  • Displaying MACRO VARIABLES VALUES in the SAS log
  • Applying quoting functions with macros
  • Incorporating SAS Macros in the DATA STEP
  • Designing macro variables during Data step Execution
  • In directing referencing Macro variables
  • Resolving Macro variables during DATA STEP EXECUTION
  • Under staining the functionality and application of the SYSMGET
  • Function and SYSMPUT routine
  • Using the INTO clause to build macro variables during PROC SQL Execution


Running Macro Programs in SAS Software:


  • Designing and implementing simple macros and reduce customizing
  • SAS application
  • To Develop Reusable Application use with MACRO
  • Specifying conditional coding inside a macro
  • The macro compilation and execution processes in the macro processor
  • SAS system options used for debugging macros
  • Reviewing error and warning log messages displayed by the macro processor
  • Designing and using macros containing parameters within them
  • Using positional and keyword parameters in macro calls
  • Difference macros and symbol table Hierarchies


Concepts in Macro Functions, Macro Interface and Macro Quoting:


  • Functions and how to use MACRO CODING
  • Techniques for Storing MACROS
  • Understanding the auto call feature
  • Permanently storing and using compiled macros
  • Writing Efficient macro programs


Debugging SAS Programs:


  • SAS programs that work
  • Fixing Programs that don’t work
  • Searching for the missing semicolon
  • Input statement reaching past the end of line
  • Lost card
  • Invalid Data
  • How to handle different kind of SAS errors
  • Missing VALUES were Generated
  • Numeric values have been converted to Character
  • WRONG results but no error message
  • The data step Debugger
  • SAS Truncated a character variable
  • SAS stops in the middle of the job
  • SAS runs pout of memory or disk space


Statistical Data Warehousing:


  • What is ETL
  • SAS/ETL Concepts
  • What is OLAP
  • SAS./OLAP Concepts
  • Role of Pass through to create Data warehousing Environment


About the Instructor

ravitej meka
repalle, India