Data Analytics with SAS Training

What is Data Analytics?

Data Analytics is the process of examining, cleaning and modelling data to obtain useful information that may suggest conclusions or support decision making. This is done with specialized systems and software. Data analytics is widely used in commercial business to obtain crucial information that will affect important decisions like where to invest and when to invest. It is also used by scientists and researchers to verify or disprove the scientific models and theories. With the increasing amount of data and the arrival of Big Data, Data analytics is becoming a Billion dollar industry with investments increasing many fold in last few years.

What is SAS?

SAS is a software developed by SAS Institute for advanced analytics in 1976. It is used to mine, manage and retrieve data from multiple sources and perform statistical analysis on it. It uses SAS language for advanced analysis. A point and click user interface for non-technical users was added in 2004. It has more than 200 components to do all sorts of data handling. SAS had developed a lot in recent years and now has an array of software products which uses statistical analysis for various purposes like fraud identification, risk modelling, scenario analysis etc.

Why to enrol in Data Analytics with SAS course at Trishana Technologies, Bangalore?

Trishana Technologies believes in pragmatic approach of teaching rather than traditional approach as all other institutes are doing. So, we installed smart classrooms and every concept in Data analytics and SAS is taught and explained with real time examples. All are theory classes are followed by practice sessions which help you to implement the concepts you learned shortly before. By this way, we ensure that you fully understand the working of the concepts and way to implement them. At Trishana Technologies, we provide unlimited time to practice in our lab since the software is not affordable by all our students. We also take classes on Statistics, SQL and Excel to give you a clear picture of Data analytics and how to do it conceptually. We ensure that when you complete our course, you will be in top ranks in the Data analytics domain with sound knowledge and superior skills.

Our Data Analytics with SAS course syllabus

Section 1
Overview of SAS

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

Section 2
Base SAS Fundamentals

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

Section 3
Data Access & Data Transformation

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

Section 4
Reading SAS data set

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

Section 5
Reading Excel worksheets

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

Section 6
Reading Raw data from External File

  • 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)

Section 7
Writing to an External file

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

Section 8
Data transformations (Data step processing)

  • 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

Section 9
Creating subset of observations using

  • Where condition
  • Conditional processing using: IF statements

Section 10
Processing Data Iteratively

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

Section 11
Summarizing data

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

Section 12
Manipulating Data

  • 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

Section 13
Restructuring a SAS data set

  • Rotating with the data step
  • Using the transpose procedure

Section 14
Combining SAS data sets

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

Section 15
SAS Access & SAS Connect

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

Analysis & Presentation

SAS/REPORTS SAS/GRAPH/STATS SAS/ODS

Section 1
Producing detailed /Summary Reports

  • 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

Section 2
Generating Statistical Reports using

  • Regression proc
  • Uni/Multivariate proc
  • Anova proc

Section 3
Generating Graphical reports using

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

Section 4
SAS/SQL Programming

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

Section 5
Basics Queries

  • 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

Section 6
Sub Queries

  • Non correlated sub queries
  • Correlated sub queries

Section 7
SQL Joins (Combining SAS data sets using SQL Joins)

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

Section 8
SET Operators

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

Section 9
Additional SQL Procedures features

  • 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

Section 10
SAS Macro Language

  • 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

Section 11
Basics Statistics

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

Career opportunities in Data Analytics with SAS

  • SAS Analyst
  • Business Analyst
  • Analyst – Data Management
  • Data Analyst
  • SAS programmer
  • Staff Accountant