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Mastering SAS Programming for Data Warehousing

Mastering SAS Programming for Data Warehousing

By : Monika Wahi
4.4 (5)
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Mastering SAS Programming for Data Warehousing

Mastering SAS Programming for Data Warehousing

4.4 (5)
By: Monika Wahi

Overview of this book

SAS is used for various functions in the development and maintenance of data warehouses, thanks to its reputation of being able to handle ’big data’. This book will help you learn the pros and cons of storing data in SAS. As you progress, you’ll understand how to document and design extract-transform-load (ETL) protocols for SAS processes. Later, you’ll focus on how the use of SAS arrays and macros can help standardize ETL. The book will also help you examine approaches for serving up data using SAS and explore how connecting SAS to other systems can enhance the data warehouse user’s experience. By the end of this data management book, you will have a fundamental understanding of the roles SAS can play in a warehouse environment, and be able to choose wisely when designing your data warehousing processes involving SAS.
Table of Contents (18 chapters)
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1
Section 1: Managing Data in a SAS Data Warehouse
7
Section 2: Using SAS for Extract-Transform-Load (ETL) Protocols in a Data Warehouse
12
Section 3: Using SAS When Serving Warehouse Data to Users

Working with other file formats

Up to now, in this chapter, we have talked about reading in SAS datasets in either XPT or *.SAS7bdat format. Now, we will examine reading in data from non-SAS formats:

  • We will start by revisiting the infile statement, and examine options that can be set to help read in non-SAS data.

  • Next, we will practice using the infile statement to read a *.csv file and a *.txt file into SAS.

  • After this, we will examine PROC IMPORT, and experiment with how it can help us read in data without having us type a lengthy infile statement.

  • Finally, we will discuss converting non-SAS data to SAS format for physical storage.

This section will provide an overview of approaches the analyst can take when reading data from non-SAS formats into SAS, and provide several examples.

Reading non-SAS data formats

With respect to the size of data files, you may have noticed that of the three formats for the Chap2_1_SAS, Chap2_1_XPT, and Chap2_1_CSV datasets...

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Mastering SAS Programming for Data Warehousing
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