You're reading from Mastering SAS Programming for Data Warehousing An advanced programming guide to designing and managing Data Warehouses using SAS

Product type Paperback

Published in Oct 2020

Publisher Packt

ISBN-13 9781789532371

Length 494 pages

Edition 1st Edition

Tools

SAS

Concepts

Application Development

Author (1):

Monika Wahi

View More author details

Table of Contents (18) Chapters

Preface

1. Section 1: Managing Data in a SAS Data Warehouse

2. Chapter 1: Using SAS in a Data Mart, Data Lake, or Data Warehouse FREE CHAPTER

3. Chapter 2: Reading Big Data into SAS

4. Chapter 3: Helpful PROCs for Managing Data

5. Chapter 4: Managing ETL in SAS

6. Chapter 5: Managing Data Reporting in SAS

7. Section 2: Using SAS for Extract-Transform-Load (ETL) Protocols in a Data Warehouse

8. Chapter 6: Standardizing Coding Using SAS Arrays

9. Chapter 7: Designing and Developing ETL Code in SAS

10. Chapter 8: Using Macros to Automate ETL in SAS

11. Chapter 9: Debugging and Troubleshooting in SAS

12. Section 3: Using SAS When Serving Warehouse Data to Users

13. Chapter 10: Considering the User Needs of SAS Data Warehouses

14. Chapter 11: Connecting the SAS Data Warehouse to Other Systems

15. Chapter 12: Using the ODS for Visualization in SAS

16. Assessments

17. Other Books You May Enjoy

Leave a review - let other readers know what you think

Using original versions of SAS

Initially, SAS data had to be input through code into memory whenever analysis code was to be run on the data. This section covers the following:

How to enter data into SAS datasets using SAS
The early PROCs developed, such as PROC PRINT and PROC MEANS
Improvements to data handling made in Base SAS

In this section, you will learn how SAS's data management processes were initially developed. The processes impact how SAS runs today.

Initial SAS data handling

As described on SAS's website (https://www.sas.com/en_us/company-information/profile.html), SAS was invented in 1966 as the Statistical Analysis System, developed under a grant from the United States (US) National Institutes of Health (NIH) to eight universities. The immediate need was to develop a computerized system that could analyze the large amount of agriculture data being collected through the US Department of Agriculture (USDA).

According to the SAS...