Data Analytics with SAS Training

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.

Curriculum

Our Data Analytics with SAS course syllabus

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?

Base SAS Fundamentals

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

Data Access & Data Transformation

Accessing SAS Data libraries
Getting familiar with SAS Data set

Reading SAS data set

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

Reading Excel worksheets

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

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)

Writing to an External file

Write data values from SAS data set to an external file

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

Creating subset of observations using

Where condition
Conditional processing using: IF statements

Processing Data Iteratively

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

Summarizing data

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

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

Restructuring a SAS data set

Rotating with the data step
Using the transpose procedure

Combining SAS data sets

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

SAS Access & SAS Connect

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

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

Generating Statistical Reports using

Regression proc
Uni/Multivariate proc
Anova proc

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

SAS/SQL Programming

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

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

Sub Queries

Non correlated sub queries
Correlated sub queries

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

SET Operators

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

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

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

Basics Statistics

Standard deviation
Correlation Coefficients
Outliers
Linear regressions
Clustering
Chi Square

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