Data Science With SAS Training in Chennai

Syllabus of Data Science with SAS Course in Chennai

• Introduction and History of SAS
• Significance of SAS software solutions in various industries
• Demonstrate SAS Capabilities
• Job Profile / career opportunities with SAS worldwide?

• Explore SAS Windowing Environment
• SAS Tasks
• Working with SAS Syntax
• Create and submit a SAS sample program

• Accessing SAS Data libraries
• Getting familiar with SAS Data set

• Introduction to reading data
• Examine structure of SAS data set
• Understanding of SAS works

• Using Excel data as input
• Create as sample program to import and export excel sheets

• Introduction to raw data
• Reading delimited raw data file (List Input)
• Using standard delimited data as input
• Using nonstandard delimited data as input
• Reading raw data aligned to columns (Fixed or column input)
• Reading raw data with special instructions (Formatted input)

• Write data values from SAS data set to an external file

• Create multiple output datasets from single SAS dataset
• Writing observations to one or more SAS datasets
• Controlling which observations and variables to be written to output data

• Where condition
• Conditional processing using: IF statements

• Iterative DO loop processing with END statement
• DO WHILE & DO UNTIL Statement
• SAS Array statement

• Creating and Accumulating total variable (Retain)
• Using Assignment statement
• Accumulating totals for a group of data (BY group)

• Sorting SAS data sets
• Manipulating SAS data values
• Presentation of user defined values /data/currency values using FORMAT procedure
• SAS functions to manipulate char and num data
• Convert data type form char-to num and num-to-char
• SAS variables lists/ SAS variables lists range
• Debugging SAS program
• Accessing observations by creating index

• Rotating with the data step
• Using the transpose procedure

• Concatenation
• Interleaving
• One to one reading
• One to one merging (with non-matching)
• Match merging (Merging types with IN=option)

• Validating and cleaning data
• Detect and correct syntax errors
• Examining data errors

• Freq Report
• Means Report
• Tabulate Report
• Proc report
• Summary report
• Univariate report
• Contents report
• Print report
• Compare proc
• Copy proc
• Datasets proc
• Proc append
• Proc delete

• Regression proc
• Uni/Multivariate proc
• Anova proc

• Producing Bar and Pie charts (GCHART Proc)
• Producing plots (GPLOT Proc)
• Presenting Output Report result in:
• PDF
• Text files
• Excel
• HTML Files

• Introduction and overview to SQL procedure
• Proc SQL and Data step comparisons

• Proc SQL syntax overview
• Specifying columns/creating new columns
• Specifying rows/subsetting on rows
• Ordering or sorting data
• Formatting output results
• Presenting detailed data
• Presenting summarized data

• Non correlated sub queries
• Correlated sub queries

• Introduction to SQL joins
• Types of joins with examples
• Simple to complex joins
• Choosing between data step merges and SQL joins

• Introduction to set operations
• Except/Intersect/Union/Outer union operator

• Creating views with SQL procedure
• Dictionary tables and views
• Interfacing Proc SQL with the macro programming language
• Creating and maintaining indexes
• SQL Pass-Through facility

• Introduction to macro facility
• Generate SAS code using macros
• Macro compilation
• Creating macro variables
• Scope or macro variables
• Global/Local Macro variables
• User defined /Automatic Macro variables
• Macro variables references
• Combing macro variables references with text
• Macro functions
• Quoting (Masking)
• Creating macro variables in Data step (Call SYMPUT Routine)
• Obtaining variable value during macro execution (SYMGET function)
• Creating macro variables during PROC SQL execution (INTO Clause)
• Creating a delimited list of values
• Macro parameters
• Strong Macro using Autocall Features
• Permanently storing and using stored compiled macro program
• SAS Macro debugging options to track problems

• Standard deviation
• Correlation Coefficients
• Outliers
• Linear regressions
• Clustering
• Chi Square