Sas 9 4 Sql Procedure User S Guide Third Edition
Download Sas 9 4 Sql Procedure User S Guide Third Edition PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Sas 9 4 Sql Procedure User S Guide Third Edition book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
SAS 9. 4 SQL Procedure User's Guide, Third Edition
Describes the basics of using the SQL procedure and provides comprehensive reference information. The usage information includes retrieving data from single and multiple tables; selecting specific data from tables; subsetting, ordering, and summarizing data; updating tables; combining tables to create new tables and useful reports; performing queries on database management system (DBMS) tables; using PROC SQL with the SAS macro facility; and debugging and optimizing PROC SQL code. The reference information includes statements, dictionary components, and system options.
SAS Data Analytic Development
Author: Troy Martin Hughes
language: en
Publisher: John Wiley & Sons
Release Date: 2016-09-19
Design quality SAS software and evaluate SAS software quality SAS Data Analytic Development is the developer’s compendium for writing better-performing software and the manager’s guide to building comprehensive software performance requirements. The text introduces and parallels the International Organization for Standardization (ISO) software product quality model, demonstrating 15 performance requirements that represent dimensions of software quality, including: reliability, recoverability, robustness, execution efficiency (i.e., speed), efficiency, scalability, portability, security, automation, maintainability, modularity, readability, testability, stability, and reusability. The text is intended to be read cover-to-cover or used as a reference tool to instruct, inspire, deliver, and evaluate software quality. A common fault in many software development environments is a focus on functional requirements—the what and how—to the detriment of performance requirements, which specify instead how well software should function (assessed through software execution) or how easily software should be maintained (assessed through code inspection). Without the definition and communication of performance requirements, developers risk either building software that lacks intended quality or wasting time delivering software that exceeds performance objectives—thus, either underperforming or gold-plating, both of which are undesirable. Managers, customers, and other decision makers should also understand the dimensions of software quality both to define performance requirements at project outset as well as to evaluate whether those objectives were met at software completion. As data analytic software, SAS transforms data into information and ultimately knowledge and data-driven decisions. Not surprisingly, data quality is a central focus and theme of SAS literature; however, code quality is far less commonly described and too often references only the speed or efficiency with which software should execute, omitting other critical dimensions of software quality. SAS® software project definitions and technical requirements often fall victim to this paradox, in which rigorous quality requirements exist for data and data products yet not for the software that undergirds them. By demonstrating the cost and benefits of software quality inclusion and the risk of software quality exclusion, stakeholders learn to value, prioritize, implement, and evaluate dimensions of software quality within risk management and project management frameworks of the software development life cycle (SDLC). Thus, SAS Data Analytic Development recalibrates business value, placing code quality on par with data quality, and performance requirements on par with functional requirements.
PROC SQL by Example
In PROC SQL by Example: Using SQL within SAS, author Howard Schreier illustrates the use of PROC SQL in the context of the SAS DATA step and other SAS procedures (such as SORT, FREQ, MEANS, SUMMARY, APPEND, DATASETS, and TRANSPOSE) whose functionality overlaps and complements that of SQL. Using a side-by-side approach, this concise reference guide includes many extensively explained examples showing equivalent DATA step and SQL code, enabling SAS users to take advantage of existing SAS skills and knowledge while learning about SQL. Discussions cover the differences between SQL and the DATA step as well as situations where SQL and the DATA step are used together to benefit from the strengths of each. Topics addressed include working with joins and merges; using subqueries; understanding set operators; using the Macro Facility with PROC SQL; maintaining tables; working with views; using PROC SQL as a report generator; and more. This text is ideal for SAS programmers seeking to add PROC SQL to their SAS toolkits as well as SQL programmers striving to better integrate the SAS DATA step and SQL. This book is part of the SAS Press program.