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Course Skill Level:

Foundational to Intermediate

Course Duration:

3 day/s

  • Course Delivery Format:

    Live, instructor-led.

  • Course Category:

    Big Data & Data Science

  • Course Code:


Who should attend & recommended skills:

Those with basic Python & spreadsheet software experience

Who should attend & recommended skills

  • Python experienced developers, analysts, or others with Python skills who want to leverage the full potential of SAS to get unique, actionable insights from your data.
  • Skill-level: Foundation-level SAS for Data Analysis skills for Intermediate skilled team members. This is not a basic class.
  • Python: Basic (1-2 years’ experience)
  • Spreadsheet software: Basic to Intermediate (1-5 years’ experience)

About this course

SAS is one of the leading enterprise tools in the world today when it comes to data management and analysis. It enables the fast and easy processing of data and helps you gain valuable business insights for effective decision-making. This course will serve as a comprehensive guide that will prepare you for the SAS certification exam. After a quick overview of the SAS architecture and components, the course will take you through the different approaches to importing and reading data from different sources using SAS. You will then cover SAS Base and 4GL, understanding data management and analysis, along with exploring SAS functions for data manipulation and transformation. Next, you’ll discover SQL procedures and get up to speed on creating and validating queries. In the concluding lessons, you’ll learn all about data visualization, right from creating bar charts and sample geographic maps through to assigning patterns and formats. In addition to this, the course will focus on macro programming and its advanced aspects. By the end of this course, you will be well versed in SAS programming and have the skills you need to easily handle and manage your data-related problems in SAS.

Skills acquired & topics covered

  • Building enterprise-class data solutions using SAS and become well-versed in SAS programming
  • Working with different data structures, and run SQL queries to manipulate your data
  • Exploring essential concepts and techniques with practical examples to confidently pass the SAS certification exam
  • Exploring a variety of SAS modules and packages for efficient data analysis
  • Using SAS 4GL functions to manipulate, merge, sort, and transform data
  • Gaining useful insights into advanced PROC SQL options in SAS to interact with data
  • Getting to grips with SAS Macro and define your own macros to share data
  • Discovering the different graphical libraries to shape and visualize data with
  • Applying the SAS Output Delivery System to prepare detailed reports

Course breakdown / modules

  • SAS dataset fundamentals
  • SAS programming language – basic syntax
  • Dataset options
  • SAS operators
  • Formats
  • Subsetting datasets
  • Dictionary tables

  • Length of a variable
  • Case conversion and alignment
  • String identification
  • Dealing with blanks
  • Missing and multiple values
  • Interval calculations
  • Concatenation
  • Logic and control
  • Number manipulation

  • Introduction to combining
  • Concatenation
  • Interleaving
  • Merging
  • Indexing
  • Encryption

  • Proc Freq
  • Proc Univariate
  • Proc Means and Summary
  • Proc Corr
  • Proc REG
  • Proc Transpose

  • What are macros?
  • Macro variable processing
  • Macro resolution tracking
  • Macro definition processing
  • Comparing positional and keywords parameters
  • Data-driven programming
  • Leveraging automatic global macro variables
  • Macros that evaluate
  • Writing efficient macros

  • Exchanging values between the DATA step and macro variables
  • Altering the CALL SYMPUT example
  • Resolving macro variables
  • Macro quoting

  • Comparing data steps and Proc SQL
  • Proc SQL joins
  • Proc SQL essentials
  • Dictionary tables

  • SAS views in Proc SQL
  • Making changes with Proc SQL
  • Identifying duplicates using Proc SQL
  • Creating an index in Proc SQL
  • Macros and Proc SQL

  • The role of data visualization in analytics
  • Histograms
  • Line plots
  • Vertical and horizontal bar charts
  • Scatter charts
  • Box plot

  • Proc Tabulate
  • Specifying the ODS destination
  • Formatting ODS files
  • ODS Excel charts