Book Image

Hands-On SAS for Data Analysis

By : Harish Gulati
Book Image

Hands-On SAS for Data Analysis

By: Harish Gulati

Overview of this book

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 book 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 book 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 chapters, 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 book will focus on macro programming and its advanced aspects. By the end of this book, 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.
Table of Contents (17 chapters)
Free Chapter
1
Section 1: SAS Basics
4
Section 2: Merging, Optimizing, and Descriptive Statistics
7
Section 3: Advanced Programming
10
Section 4: SQL in SAS
13
Section 5: Data Visualization and Reporting

Dataset options

There are many built-in SAS options that apply to the dataset. The broad purpose of these options is to help us do the following:

  • Rename variables
  • Select variables for subsetting
  • Retain select variables
  • Specify the password for a dataset, compress it, and encrypt it

Throughout this book, we will be looking at various dataset options. We will begin by exploring the compress, encrypt, and index options.

Compression

Compression reduces the number of bytes that are required to store each observation. The advantage of compression is that it requires less storage, owing to the fact that fewer bytes are required and fewer I/O operations are necessary to read or write to the data during processing.

The biggest disadvantage...