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  • Book Overview & Buying Mastering SAS Programming for Data Warehousing
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Mastering SAS Programming for Data Warehousing

Mastering SAS Programming for Data Warehousing

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

Mastering SAS Programming for Data Warehousing

4.4 (5)
By: Monika Wahi
Buy this Book

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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Preface
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Preface
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Who this book is for
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What this book covers
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To get the most out of this book
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Download the example code files
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Download the color images
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Conventions used
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Get in touch
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Reviews
1
Section 1: Managing Data in a SAS Data Warehouse
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Section 1: Managing Data in a SAS Data Warehouse
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2
Chapter 1: Using SAS in a Data Mart, Data Lake, or Data Warehouse
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Chapter 1: Using SAS in a Data Mart, Data Lake, or Data Warehouse
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Technical requirements
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Using original versions of SAS
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Accessing data in SAS
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Improving I/O
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Dealing with storage and memory issues
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Using SAS in modern warehousing
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Summary
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Questions
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Further reading
3
Chapter 2: Reading Big Data into SAS
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Chapter 2: Reading Big Data into SAS
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Technical requirements
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Reading data extracts into SAS
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Using the SAS XPT format
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Working with other file formats
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Dealing with difficult data
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Summary
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Questions
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Further reading
4
Chapter 3: Helpful PROCs for Managing Data
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Chapter 3: Helpful PROCs for Managing Data
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Technical requirements
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PROCs for understanding data
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Using labels and formats in processing
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Viewing data in SAS
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Summary
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Questions
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Further reading
5
Chapter 4: Managing ETL in SAS
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Chapter 4: Managing ETL in SAS
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Technical requirements
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Setting up an analytic environment
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Planning for data transformation
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Developing policy
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Summary
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Questions
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Further reading
6
Chapter 5: Managing Data Reporting in SAS
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Chapter 5: Managing Data Reporting in SAS
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Technical requirements
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Using the ODS for data files
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Using the ODS for graphics files
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SAS PROCs designed for reporting
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Summary
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Questions
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Further reading
7
Section 2: Using SAS for Extract-Transform-Load (ETL) Protocols in a Data Warehouse
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Section 2: Using SAS for Extract-Transform-Load (ETL) Protocols in a Data Warehouse
8
Chapter 6: Standardizing Coding Using SAS Arrays
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Chapter 6: Standardizing Coding Using SAS Arrays
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Technical requirements
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Understanding examples of arrays used to create variables
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Conditions and index variables in array processing
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Limitations of arrays
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Summary
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Questions
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Further reading
9
Chapter 7: Designing and Developing ETL Code in SAS
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Chapter 7: Designing and Developing ETL Code in SAS
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Technical requirements
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Planning the ETL approach
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Creating transformation code
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Summary
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Questions
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Further reading
10
Chapter 8: Using Macros to Automate ETL in SAS
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Chapter 8: Using Macros to Automate ETL in SAS
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Technical requirements
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Creating macros out of data step code
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Storing and calling macros
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Loading transformed data
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Summary
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Questions
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Further reading
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Chapter 9: Debugging and Troubleshooting in SAS
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Chapter 9: Debugging and Troubleshooting in SAS
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Technical requirements
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Debugging data step code
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Debugging the do loop code
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Debugging SAS macros
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Summary
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Questions
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Further reading
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Section 3: Using SAS When Serving Warehouse Data to Users
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Section 3: Using SAS When Serving Warehouse Data to Users
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Chapter 10: Considering the User Needs of SAS Data Warehouses
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Chapter 10: Considering the User Needs of SAS Data Warehouses
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Technical requirements
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Needs of data warehouse users
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Data stewardship for serving warehouse users
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Data stewardship for serving warehouse developers
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Summary
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Questions
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Further reading
14
Chapter 11: Connecting the SAS Data Warehouse to Other Systems
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Chapter 11: Connecting the SAS Data Warehouse to Other Systems
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Technical requirements
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Serving SAS to other systems
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Connecting to non-SAS data storage
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Innovations in integrating SAS in reporting functions
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Summary
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Questions
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Further reading
15
Chapter 12: Using the ODS for Visualization in SAS
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Chapter 12: Using the ODS for Visualization in SAS
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Technical requirements
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The basics of using the ODS for data visualization
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Serving SAS data to the web with the ODS
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Using SAS and R for visualizations
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Considerations when reporting SAS warehouse data
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Summary
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Questions
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Further reading
16
Assessments
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Chapter 1
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Chapter 2
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Chapter 3
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Chapter 4
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Chapter 5
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Chapter 6
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Chapter 7
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Chapter 8
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Chapter 9
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Chapter 10
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Chapter 11
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Chapter 12
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Chapter 4

  1. Data transfers direct from the data provider must be stored in a highly secure environment because they often contain sensitive data that is necessary to have during transformation, but will be removed before the data is loaded into the warehouse, mart, or lake.

  2. Maintaining modular, systematically named code files, rather than one long code file, allows the opportunity for manual rollback. This makes troubleshooting to repair variables easier if a problem is identified after processing.

  3. The main advantage of naming these variables COST1, COST2, and so on up to COST10 is that they could be easily declared in an array by using the range COST1-COST10. The main disadvantage of renaming these variables with names such as COST1 and COST2 is that the variable names would become unintuitive and documentation would be needed in order to understand what they mean.

  4. Formats can be created in SAS using PROC FORMAT and saved outside of the data step code. In contrast,...

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Mastering SAS Programming for Data Warehousing
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