SAS Training for SAS BASE Certification - Hyderabad, India

1. Fundamentals and environment of SAS
2. Getting to know SAS Enterprise Guide
3. Creation, compilation and execution of SAS datasets
4. Creating and analyzing graphs and reports
5. In-depth study of SAS Base and SAS Advanced
6. Logical operators, statements and functions

• Business Intelligence professionals
• Software developers and architects
• Project managers
• ETL, SQL, data warehouse and analytics professionals
• Mainframe and testing professionals
• Graduates wanting to enter Big Data analytics

Anybody can learn SAS and get trained. Having a basic knowledge of SQL can help.

Hyderabad is the second most dynamic city in India with booming IT sector. This city comprises of all sorts of tech firms small and big thriving in this market. With the growing unpredictability of economy and business conditions, companies are increasingly relying on research and analytics. Due to this SAS software stack has become a preferred tool for the Hyderabad-based companies generating lucrative career opportunity for the aspirants in this city.

With the emergence of big data more and more companies are adopting tools and technologies to comprehend and decode this humongous amount of data. SAS is one of those technologies which have successfully served this purpose. Therefore the companies in Hyderabad are hiring SAS professionals with attractive salary packages.

• 70% of companies say analytics is integral to how they make decisions – IBM Study
• Most companies estimate they’re analyzing a mere 12% of the data they have – Forrester Research
• A Principal SAS Programmer in United States can earn up to $102,000 –indeed.com

Intellipaat’s SAS Training Course helps you gain expertise in SAS through interactive classrooms, lab practice sessions and real-time projects. Also this training program helps you qualify for SAS Certified Base Programmer Exam with good scores. Hence enroll in SAS Training Course and give a head start to your career.

Bangalore, Melbourne, Chicago, San Francisco, London, Toronto, New York, India

Installation and introduction to SAS, how to get started with SAS, understanding the different SAS Windows, how to work with data sets, the various SAS Windows like Output, Search, Editor, Log, Explorer, understanding the SAS Functions, which are the various Library Types and programming files

How to import and export raw data files, how to read and subset the data sets, the different statements like SET, MERGE, WHERE

Hands-on Exercise – How to import the Excel file in the Workspace, how to read data and exporting the Workspace to save the data

The different SAS Operators like Logical, COmparison, Arithmetic, deploying the different SAS Functions like Character, Numeric, Is Null, Contains, Like, Input/Output, along with the conditional statements like If/Else, Do While, Do Until and so on.

Hands-on Exercise – Performing operations using the SAS Functions, logical and arithmetic operations.

Understanding about Input Buffer, PDV (Backend), learning what is Missover

Defining and Using KEEP and DROP statements, apply these statements, Format and Labels in SAS.

Hands-on Exercise – Use KEEP and DROP statements

Understanding Delimiter, dataline rules, DLM, Delimiter DSD, raw data files and execution, list input for standard data.

Hands-on Exercise – Use delimiter rules on raw data files

The various SAS standard Procedures built-in for popular programs – PROC SORT, PROC FREQ, PROC SUMMARY, PROC RANK, PROC EXPORT, PROC DATASET, PROC TRANSPOSE, , PROC CORR etc.

Hands-on Exercise – Use SORT, FREQ, SUMMARY, EXPORT and other procedures

Reading standard and non-standard numeric inputs with Formatted inputs, Column Pointer Controls, Controlling while a record loads, Line pointer control / Absolute line pointer control, Single Trailing , Multiple IN and OUT statements, DATA LINES statement and rules, List Input Method, comparing Single Trailing and Double Trailing.

Hands-on Exercise – Read standard and non-standard numeric inputs with Formatted inputs, Control while a record loads, Control a Line pointer, Write Multiple IN and OUT statements

SAS FORMAT statements – standard and user-written, associating a format with a variable, working with SAS FORMAT, deploying it on PROC Data sets, comparing ATTRIB and FORMAT statements.

Hands-on Exercise – Format a variable, deploy format rule on PROC DATA set, Use ATTRIB statement

Understanding PROC GCHART, various Graphs, Bar Charts – Pie, Bar, 3D, plotting variables with PROC GPLOT.

Hands-on Exercise – Plot graphs using PROC GPLOT Display charts using PROC GCHART

SAS advanced data discovery and visualization, point-and-click analytics capabilities, powerful reporting tools.

Character Functions, Numeric Functions, Converting Variable Type.Hands-on Exercise – Use Functions in data transformation

Introduction to ODS, Data Optimization, How to generate files (rtf, pdf, html, doc) using SAS

Hands-on Exercise – Optimize data, generate rtf, pdf, html and doc files

Macro Syntax, Macro Variables, Positional Parameters in a Macro, Macro Step

Hands-on Exercise – Write a macro, Use positional parameters

SQL Statements in SAS, SELECT, CASE, JOIN, UNION, Sorting Data

Hands-on Exercise – Create sql query to select and add a condition
Use a CASE in select query

Base SAS web-based interface and ready-to-use programs, advanced data manipulation, storage and retrieval, descriptive statistics.

Hands-on Exercise – Use web UI to do statistical operations

Report Enhancement, Global Statements, User-defined Formats, PROC SORT, ODS Destinations, ODS Listing, PROC FREQ, PROC Means, PROC UNIVARIATE, PROC REPORT, PROC PRINT

Hands-on Exercise – Use PROC SORT to sort the results, List ODS, Find mean using PROC Means, print using PROC PRINT

Project 1 – Categorization of patients based on count of drugs for their therapy

Domain: Health Care

Objective – This project aims to find out descriptive statistics & subset for specific clinical data problems. It will give them brief insight about BASE SAS procedures and data steps.

Problem Statement :

Count the number of patients and list of those patients

1. Who were ever on at least one of the four drugs
2. Who were ever on each of the four drugs
3. Who had never been on any drug

Output should be four datasets

1. TYPA – Contains the list of patients from problem 1
2. TYPB – Contains the list of patients from problem 2
3. TYPC – Contains the list of patients from problem 3
4. SUMMARY – – Contains the summary of counts for each of 3 problems