The document outlines the contents of a DV Analytics training package, including courses in SAS programming, SQL, macro processing, advanced programming techniques, Excel, Access, and data analytics. Key topics covered are SAS base programming, data manipulation, summary reports, SQL processing, macro processing, advanced techniques, Excel basics and advanced functions, Access basics and advanced queries, and descriptive statistics, regression, and other analytic methods. Courses are hands-on with practical projects. Contact information is provided at the end.

1. DV Analytics Training Package
dvanalytics.training@gmail.com

3. Course Contents
• SAS Base Programming:
• SAS Programming 1:
• Introduction SAS system and Getting Familiar to SAS environment
• Creating Libraries and Datasets using Data Step
• Producing List Reports using Proc Step
• Data Manipulation Techniques using
• Data Step Vs Proc Step
• Format Vs Informat
• Reading raw data files using Infile and Proc Import statement
• PDV
• Examining Errors in SAS programing
• Conditional processing using If, Where, Keep, Drop statement
• Remove Duplicate records using Proc Sort
• Combining SAS dataset using SAS Merge and Set statement
•
• Summary Reports
– Proc Means, Proc Freq, Proc Summary, Proc Univariate, Proc Report, Proc Tabulate

4. Course Contents
• SAS Programming 2:
• Introduction to Base SAS programming with Statements, Options and Functions
• Controlling Input and Output observation
• Data Manipulation Techniques using
– Writing Multiple Dataset
– Data Transformation
• Transposing and Expanding Dataset
• SAS Functions (Numeric and Character)
– Writing to External File
– Creating An Accumulating Total Variable
– Combining Duplicate Records Using First. And Last.
– Reading Delimited Raw Data File in .txt (text File),.csv (CSV File),.xlsx (Excel File) and .accdb
(Access Database)
• DSD, DLM, MISSOVER,TRUNCOVER,STOPOVER and FLOWOVER options used in reading raw data file
– Connecting SAS to Other Database Server
– Debugging Techniques
• Put Statement
• Debug Options
• Processing Data Interactively
• DO Loop
• SAS Arrays

5. Course Contents
• SAS SQL Processing
• Accessing Data Using SQL
• Generate detail reports by working with a single table or joining tables using PROC SQL and the
appropriate options
• Generate summary reports by working with a single table or joining tables using PROC SQL and the
appropriate options
• Construct sub queries within a PROC SQL step
• Compare solving a problem using the SQL procedure versus using traditional SAS programming
techniques
• Access Dictionary Tables using the SQL procedure
• Demonstrate advanced PROC SQL skills by creating and updating tables, updating data values,
working with indexes using the macro interface/creating macro variables with SQL, defining
integrity constraints, SQL views and SET operators
• Macro Processing
• Creating and using user-defined and automatic macro variables within the SAS Macro Language
• Automate programs by defining and calling macros using the SAS Macro Language
• Understand the use of macro functions
• Recognize various system options that are available for macro debugging and displaying values of
user-defined and automatic macro variables in the SAS log

6. Course Contents
• Advanced Programming Techniques
• Demonstrate advanced data set processing techniques such as updating master
data sets, transposing data, combining/merging data, sampling data, using
generation data sets, integrity constraints and audit trails
• Reduce the space required to store SAS data sets and numeric variables within SAS
data sets by using compression techniques, length statements or DATA step views
• Develop efficient programs by using advanced programming techniques such as
permanent formats and array processing
• Use SAS System options and SAS data set options for controlling memory usage
• Control the processing of variables and observations in the DATA step
• Create sorted or indexed data in order to avoid unnecessary sorts, eliminate
duplicate data and to provide more efficient data access and retrieval
• Use PROC DATASETS to demonstrate advanced programming skills (e.g. renaming
columns, displaying metadata, creating indexes, creating integrity constraints,
creating audit trails)
• SAS Project-Practical

7. Course Contents
• Excel Base:
• Introduction MS Excel
• Navigation technique in Excel
– Cells Reference, Range, Rows and Columns
– Format Paint, Border Style and Designing, Cell Merging, Conditional Formatting, Sorting and filtering, Data
Validation, Data consolidation
– Data Import and Export
– Basic Pivot Table, Chart
– Excel Formulas and Functions like IF and Nested IF, Vlook-up, HLook-up, Sum,Sum IF,Match, Offset and
Index etc.
– Running Manual Excel Macro and Recording
• Excel Advanced:
• Advanced Data Manipulation Techniques
– Advanced Pivot Design
– Advanced Pivot Options for reporting
– Power Pivot technique
• Excel Dashboard using Excel functions and VBA Macros
• Excel VBA Programming
•
• Excel Project-Practical

8. Course Contents
• ACCESS Base and Advanced:
• Introduction MS ACCESS
• Navigation technique in ACCESS and Access Objects
– Creating Database, Tables, Field Properties
– Access Queries (Select, Make Table, Append, Update, Delete,
Crosstab, Union and Union All)
– Data Import and Export in Access
– Access Pivot Table, Chart
– Access Join
– Forms and Reports
– Access Formulas and Functions
– Access Modules using Access VBA
– Access Data Manipulation technique using SQL queries
• Access Project-Practical

9. Basic and Advanced Data analytics
• Introduction to basic descriptive statistics
• Introduction to basic statistical analysis
– Hands-on exercises
• Data exploration & Data preparation
– Hands-on exercises
• Linear Regression model building
– Hands-on exercises on simple linear model
– Hands-on exercises on multiple linear models
• Logistic Regression model building
– Hands-on exercises on Logistic Regression
• Customer segmentation using cluster analysis
– Hands-on exercises on sample data
• Decision tree models
– Hands on exercises on sample data
• Hypothesis testing with examples
– Hands on exercises on sample data
• Time series forecasting
– Hands on excesses on prediction
• Step by step process of credit risk model building

10. Contact us
• dvanalytics.training@gmail.com
• http://dvanalyticstraininginstitute.blogspot.in
• https://www.facebook.com/DvAnalyticsTrainingInstitute
• 9591793303
• Koramangala 1st block, Jakasandra,Near HDFC
Bank,Bangalore-560034