Big Data Analytics with SAS: Get actionable insights from your Big Data using th电子书

Big Data Analytics with SAS

Title Page

Big Data Analytics with SAS

Credits

Foreword

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Dedication

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

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

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

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

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

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

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

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

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