Big data analytics with SAS get actionable insights from your Big Data using the power of SAS
Leverage the capabilities of SAS to process and analyze Big Data About This Book Combine SAS with platforms such as Hadoop, SAP HANA, and Cloud Foundry-based platforms for effecient Big Data analytics Learn how to use the web browser-based SAS Studio and iPython Jupyter Notebook interfaces with SAS...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham, England ; Mumbai, [India] :
Packt
2017.
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630436106719 |
Tabla de Contenidos:
- 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
- GatherIQ™ - get involved in crowdsourcing to solve social issues
- References
- Summary
- Index.
