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

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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

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To get the most out of this book

You will need access to a version of SAS. If you do not have access to a SAS server environment or PC SAS, you can use the free version of SAS, called SAS University Edition (available here: https://www.sas.com/en_us/software/university-edition/download-software.html). SAS University Edition is available for Windows, macOS, and Linux. All code examples have been tested using SAS University Edition in Windows, but they should work on any version of SAS.

Example data curation files in this book were developed using Microsoft Word, Excel, and PowerPoint. These files can be developed in the same or comparable software.

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying/pasting of code.

You may benefit from following the author on YouTube (https://www.youtube.com/channel/UCCHcm7rOjf7Ruf2GA2Qnxow) and LinkedIn (https://www.linkedin.com/in/dethwench/), where she posts video tutorials and information about data science.