Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering SAS Programming for Data Warehousing

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

Arrow left icon
Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781789532371
Length 494 pages
Edition 1st Edition
Tools
Arrow right icon
Author (1):
Arrow left icon
Monika Wahi Monika Wahi
Author Profile Icon Monika Wahi
Monika Wahi
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

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

Chapter 7

  1. An analyst gains knowledge of what each variable means and what each level of each categorical variable means in a dataset from reviewing the data dictionary for that dataset. If the dataset is derived from survey responses, a codebook should also be included in the warehouse data curation.

  2. When preparing continuous data for processing into a data warehouse, it is necessary to know all possible values in the continuous variables, and that information is not available in PROC UNIVARIATE output. Using PROC FREQ on a continuous variable allows the analyst the ability to view the existence and distribution of every single value in the continuous variable. Although the output is very long, viewing the top and bottom of the output (extreme values) can provide instructive information about how to optimally process the variable into the warehouse.

  3. It is helpful to plan transformed variables in a data dictionary before creating ETL code for them for a few reasons. First...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image