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Mastering SAS Programming for Data Warehousing

Name: Mastering SAS Programming for Data Warehousing
Author: Monika Wahi
ISBN: 9781789532371

by Monika Wahi

October 2020

Beginner to intermediate

494 pages

12h 14m

English

Packt Publishing

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Mastering SAS Programming for Data Warehousing
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Preface
Who this book is forWhat this book coversTo get the most out of this bookDownload the example code filesDownload the color imagesConventions usedGet in touchReviews
Section 1: Managing Data in a SAS Data Warehouse
Chapter 1: Using SAS in a Data Mart, Data Lake, or Data Warehouse
Technical requirementsUsing original versions of SASInitial SAS data handlingEarly SAS data handlingSAS data handling improvementsAccessing data in SASUpgrading to mainframesTransitioning to personal computersReading external filesImproving I/ODeveloping warehouse environmentsUsing the WHERE clauseUsing IF compared to WHERESorting in SASSetting indexes on variablesDealing with storage and memory issuesAvoiding memory issuesAccommodating Structured Query LanguageUsing PROC SQLUsing SAS today in a warehouse environmentUsing SAS in the cloudUsing SAS in modern warehousingWarehousing unstructured textUsing SAS components for warehousingUsing other applications with SASConnecting to SnowflakeSummaryQuestionsFurther reading
Chapter 2: Reading Big Data into SAS
Technical requirementsReading data extracts into SASUnderstanding SAS datasetsWorking with the WORK directorySpecifying LIBNAMEReading in SAS datasetsUsing the SAS XPT formatStoring data in XPT formatCreating an XPT fileComparing PROC CPORT/CIMPORT to PROC COPYReading in XPTs using the XPORT engineWorking with other file formatsReading non-SAS data formatsUsing PROC IMPORTConverting non-SAS data to SAS formatDealing with difficult dataUnderstanding legacy dataReading data with difficult formatsSpecifying data locations in a fixed-width fileTroubleshooting reading data after transportSummaryQuestionsFurther reading
Chapter 3: Helpful PROCs for Managing Data
Technical requirementsPROCs for understanding dataUsing PROC CONTENTS to understand dataDocumenting SAS data with codebooksUsing labels for variablesAdding user-defined formats to categorical variablesUsing native SAS formats with numeric variablesApplying user-defined formats to continuous variablesUsing labels and formats in processingUsing PROCs with labels and formatsMaintaining labels and formatsAlternatives to using labels and formats in a warehouse settingViewing data in SASUsing PROC PRINT to view dataUsing PROC SQL to view dataUsing arithmetic operators in SASViewing data through SAS windowsSummaryQuestionsFurther reading
Chapter 4: Managing ETL in SAS
Technical requirementsSetting up an analytic environmentDesignating storage and user groupsManaging documentation storageSetting naming conventions for datasetsPlanning for data transformationUnderstanding arrays in SASSetting naming conventions for variablesSetting naming conventions and style for codeDeveloping policySetting format and label policiesSetting data transfer policiesSetting other policiesSummaryQuestionsFurther reading
Chapter 5: Managing Data Reporting in SAS
Technical requirementsUsing the ODS for data filesIdentifying available tables in the ODSIdentifying internal tables in the logOutputting internal tables using the ODSUsing the ODS for graphics filesOutputting graphics from analytic PROCsOutputting graphics in different formatsSetting system optionsSAS PROCs designed for reportingUsing PROC REPORTUnderstanding the basics of PROC TABULATEPreparing data for PROC TABULATEFormulating PROC TABULATE codeUsing PROC SGPLOTUsing PROC SGPANEL and PROC SGSCATTERUsing PROC TEMPLATE with PROC SGRENDERSummaryQuestionsFurther reading
Section 2: Using SAS for Extract-Transform-Load (ETL) Protocols in a Data Warehouse
Chapter 6: Standardizing Coding Using SAS Arrays
Technical requirementsUnderstanding examples of arrays used to create variablesScenarios where arrays are usefulArrays as temporary objectsUsing arrays to create variablesConditions and index variables in array processingAdding a condition to array processingCreating index variables from array outputsDocumenting and standardizing array processingLimitations of arraysNaming limitations in SAS arraysNaming limitations arrays impose on data storageDifficulty in troubleshootingSummaryQuestionsFurther reading

Chapter 7: Designing and Developing ETL Code in SAS
Technical requirementsPlanning the ETL approachSpecifying data with a data dictionaryUnderstanding default PROC FREQUsing options to manipulate PROC FREQ outputUsing PROC UNIVARIATE for troubleshootingUsing PROC FREQ to troubleshoot continuous variablesMaking plots for troubleshootingChoosing variables to serve to usersCreating and maintaining formats for variablesCreating transformation codeDesigning categorical grouping variablesCleaning up continuous variablesDesigning indicator variablesConsidering dates and numerical variablesExporting the transformed datasetSummaryQuestionsFurther reading
Chapter 8: Using Macros to Automate ETL in SAS
Technical requirementsCreating macros out of data step codeChoosing to use macros and macro variablesUsing macro variables with the %LET commandUsing the log file with macro variables and macrosMaking macros with PROCsMaking macros with data stepsAddition conditions to macrosStoring and calling macrosStoring and calling macros in the same codeStoring macros separately and calling them from codeLoading transformed dataSummaryQuestionsFurther reading
Chapter 9: Debugging and Troubleshooting in SAS
Technical requirementsDebugging data step codeWriting well-formed and well-formatted codeUsing log information as guidanceTroubleshooting strategies for data stepsDebugging the do loop codeUsing the original data step debuggerUsing the data step debugger in SAS Enterprise GuideDebugging SAS macrosAvoiding errors through the design processUsing %PUT to display values of macro variablesSetting system options to help with debugging macrosSummaryQuestionsFurther reading
Section 3: Using SAS When Serving Warehouse Data to Users
Chapter 10: Considering the User Needs of SAS Data Warehouses
Technical requirementsNeeds of data warehouse usersConsidering classes of data warehouse usersConsidering the needs of each class of usersData stewardship for serving warehouse usersProviding data accessServing needs created through the warehouse structureAdding, using, and serving up foreign keysCrosswalking data over timeData stewardship for serving warehouse developersManaging a data stewardship committeeProviding curation and other supportSummaryQuestionsFurther reading
Chapter 11: Connecting the SAS Data Warehouse to Other Systems
Technical requirementsServing SAS to other systemsImplementing de-identification policiesServing up a star schemaConnecting to non-SAS data storageUnderstanding SQL viewsUsing SAS to copy data from a remote data systemLeveraging PROC SQL views for data transferExporting SAS data to non-SAS data storageInnovations in integrating SAS in reporting functionsSummaryQuestionsFurther reading
Chapter 12: Using the ODS for Visualization in SAS
Technical requirementsThe basics of using the ODS for data visualizationUsing macros in reportingConnecting to data in SnowflakeServing SAS data to the web with the ODSInteracting with SAS data over the webUsing the SAS Enterprise GuideUsing SAS ViyaUsing SAS and R for visualizationsReporting SAS data in TableauConsiderations when reporting SAS warehouse dataSummaryQuestionsFurther reading
Assessments
Chapter 1Chapter 2Chapter 3Chapter 4Chapter 5Chapter 6Chapter 7Chapter 8Chapter 9Chapter 10Chapter 11Chapter 12
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Overview

"Mastering SAS Programming for Data Warehousing" dives into the effective use of SAS for handling large-scale data environments like data warehouses and data lakes. You will learn to design and manage ETL processes using SAS, standardize workflows with macros and arrays, and connect SAS to other systems to enhance reporting and data visualization.

What this Book will help me do

Master efficient data input/output management in SAS environments.
Design and maintain robust ETL pipelines using SAS macros and arrays.
Identify and address data warehouse user requirements.
Utilize Output Delivery System (ODS) to create professional reports.
Integrate SAS with external systems for optimized data processing.

Author(s)

Monika Wahi brings extensive SAS programming experience coupled with a strong background in data warehousing and data analysis. Her insightful approach demystifies complex topics, focusing on equipping readers with practical skills. Her collaborative writing style makes advanced concepts accessible and applicable to real-world scenarios.

Who is it for?

This book is designed for data professionals such as architects, managers leading data-intensive projects, and SAS programmers or developers. It's ideal for those with foundational SAS experience who aspire to manage, maintain, or develop data lakes, marts, or warehouses effectively. The book offers a logical progression from basic concepts to advanced implementations, tailored for ambitious learners.

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