Big Data Analytics with SAS
Get actionable insights from your Big Data using the power of SAS
1st Edition
Published on 13. January 2025
266 pages
978-1-78829-431-7 (ISBN)
Description
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Content
- Cover
- Title Page
- Copyright
- Credits
- Foreword
- About the Author
- About the Reviewer
- www.PacktPub.com
- Customer Feedback
- Dedication
- Table of Contents
- Preface
- Chapter 1: Setting Up the SAS® Software Environment
- What does SAS do?
- What is your perception of SAS?
- Let's get started with your free version of SAS
- History of SAS interfaces
- SAS Studio web-based GUI
- Describing the rest of SAS Studio
- SAS Studio section - Server Files and Folders
- SAS Studio section - Tasks and Utilities
- SAS Studio section - Snippets
- SAS Studio section - Libraries
- SAS Studio section - File Shortcuts
- SAS programming language
- First SAS data step program
- First use of a SAS PROC
- Saving a SAS program
- Creating a new SAS program
- The AUTOEXEC file
- Visual Programmer versus SAS Programmer
- What's in the SAS® University Edition?
- Different levels of the SAS analytic platform
- SAS data storage
- The SAS dataset
- The SAS® Scalable Performance Data Engine
- The Scalable Performance Data Server
- SAS HDAT
- SAS formats and informats
- Date and time data
- Summary
- Chapter 2: Working with Data Using SAS® Software
- Preparing data for analytics
- Making data in SAS
- Data step code to make data
- PROC SQL to make data
- Working with external data
- Data step code for importing external data
- PROC IMPORT
- Referencing external files
- Directly referencing external files
- Indirectly referencing external files
- Specialty PROCs for working with external data
- PROC HADOOP and PROC HDMD
- PROC JSON
- Specialty PROCs for working with computer languages
- PROC GROOVY
- PROC LUA
- Summary
- Chapter 3: Data Preparation Using SAS Data Step and SAS Procedures
- Data preparation for analytics
- Creating indicators for the first and last observation in a by group
- Transposing
- PROC TRANSPOSE
- SAS Studio Transpose Data task
- Statistical and mathematical data transformations
- PROC MEANS
- Imputation
- Identifying missing values
- Characterizing data
- List Table Attributes
- SAS macro facility
- Macro variables
- Macros
- Summary
- Chapter 4: Analysis with SAS® Software
- Analytics
- Descriptive and predictive analysis
- Descriptive analysis
- PROC FREQ
- PROC CORR
- PROC UNIVARIATE
- Predictive analysis
- Regression analysis
- PROC REG
- Forecasting analysis
- PROC TIMEDATA
- PROC ARIMA
- Optimization analysis
- SAS/IML
- Interacting with the R programming language
- PROC IML
- Summary
- Chapter 5: Reporting with SAS® Software
- Reporting
- SAS Studio tasks and snippets that generate reports and graphs
- BASE procedures designed for reporting
- TABULATE procedure examples
- REPORT procedure example
- The Output Delivery System
- ODS Tagsets
- ODS trace
- ODS document and the DOCUMENT procedure
- ODS Graphics
- How to make a user-defined snippet
- Summary
- Chapter 6: Other Programming Languages in BASE SAS® Software
- The DS2 programming language
- When to use DS2
- How is DS2 similar to the data step?
- How are DS2 and DATA step different?
- Programming in DS2
- DS2 methods
- DS2 system methods
- DS2 user-defined methods
- DS2 packages
- DS2 predefined packages
- DS2 user-defined packages
- Running DS2 programs
- The DS2 procedure
- DS2 Hello World program - example 1
- DS2 Hello World program - example 2
- DS2 Hello World program - example 3
- DS2 Hello World program - example 4
- DS2 Hello World program - example 5
- DS2 program with a method that returns a value
- DS2 program with a user-defined package
- The FedSQL programming language
- How to run FedSQL programs
- FedSQL program using the FEDSQL procedure
- Using FedSQL with DS
- Summary
- Chapter 7: SAS® Software Engineers the Processing Environment for You
- Architecture
- The SAS platform
- Service-Oriented Architecture and microservices
- Differences between SOA and microservices
- SAS server versus a SAS grid
- In-database processing
- In-database procedures
- Additonal in-database processing SAS offerings
- SAS Scoring Accelerator
- SAS Code Accelerator
- In-memory processing
- SAS High-Performance Analytics Server
- SAS LASR Analytics Server
- SAS Cloud Analytics Server
- Dedicated hardware for in-memory processing
- Open platform and open source
- Running SAS from an iPython Jupyter Notebook
- SAS running in a cloud
- A public cloud
- A private cloud
- A hybrid cloud
- Running SAS processing outside the SAS platform
- The SAS Embedded Process
- The SAS Event Stream Processing engine
- SAS Viya the newest part of the SAS platform
- SAS Viya programming
- SAS Viya-based solutions
- Summary
- Chapter 8: Why SAS Programmers Love SAS
- Why SAS programmers love SAS
- Examples of why SAS programmers love SAS
- Additional coding examples
- The COMPARE procedure
- The OPTIONS procedure
- Analytics is a great career
- Analytics Center of Excellence
- The executive sponsor
- The data scientist
- The data manager
- The business analyst
- The ACE leader
- Where should an ACE be located?
- Analytics across industries
- Analytics improving healthcare
- Analytics improving government services
- Analytics in financial services
- Analytics in energy
- Analytics in manufacturing
- Analytics are great for society
- Project Data Sphere®
- SAS and Data4Good
- GatherIQT - get involved in crowdsourcing to solve social issues
- References
- Summary
- Index
