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Author: Troy Martin Hughes Publisher: John Wiley & Sons ISBN: 111924076X Category : Computers Languages : en Pages : 624
Book Description
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.
Author: Troy Martin Hughes Publisher: John Wiley & Sons ISBN: 111924076X Category : Computers Languages : en Pages : 624
Book Description
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.
Author: Matthew Windham Publisher: SAS Institute ISBN: 1635267099 Category : Computers Languages : en Pages : 193
Book Description
Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data. This book covers the five critical elements of entity extraction, unstructured data, entity resolution, entity network mapping and analysis, and entity management. By following examples of how to apply processing to unstructured data, readers will derive tremendous long-term value from this book as they enhance the value they realize from SAS products.
Author: Publisher: ISBN: 9781642954821 Category : Languages : en Pages : 108
Book Description
SAS provides many different solutions to investigate and analyze text and operationalize decisioning. Several impressive papers have been written to demonstrate how to use these techniques. We have carefully selected a handful of these from recent Global Forum contributions to introduce you to the topic and let you sample what each has to offer. Also available free as a PDF from sas.com/books.
Author: Troy Martin Hughes Publisher: Createspace Independent Publishing Platform ISBN: 9781726497732 Category : Languages : en Pages : 372
Book Description
SAS(R) Data-Driven Development is the only comprehensive text that demonstrates how to build dynamic SAS software driven by control data. Data-driven design enables developers to create flexible, reusable software that adapts to diverse industries, organizations, and data sources because business rules, data mappings, formatting, report style, program logic, and other dynamic elements are maintained as external control data — not as static code. Data-driven design is the key to unlocking highly configurable, "codeless" software that developers, SAS administrators, end users, and other stakeholders can reuse and configure — without modifying one line of code! This text introduces high-level design concepts, patterns, and principles, after which real-world scenarios demonstrate SAS development best practices: Part I. Data-Driven Design: Learn how to harness procedural abstraction, data abstraction, iteration abstraction, software modularity, and data independence, with concepts drawn from object-oriented programming (OOP), master data management (MDM), table-driven design, and business rules engines. Part II. Control Data: Understand the limitless data structures that can drive SAS software, including parameters, configuration files, control tables, decision tables, SAS data sets, SAS arrays, and CSV, Excel, XML, and CSS files. Interoperability is modeled through control data that can be accessed by SAS and other applications. Throughout the text, requirements-based examples demonstrate data analysis, data modeling, data mapping, data governance, dynamic "traffic light" reporting, and other use cases. Examples contrast concrete, code-driven design with abstract, data-driven design to illustrate the clear advantages of the latter. Application of the SAS Macro Language often signifies the first milestone in a SAS practitioner's career — because macros facilitate flexible, reusable software. Data-driven design represents the next milestone and this text provides the guidebook for that incredible journey. Start your journey today!
Author: Olivia Parr-Rud Publisher: SAS Institute ISBN: 1629593273 Category : Business & Economics Languages : en Pages : 182
Book Description
This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. This beginnner's guide with clear, illustrated, step-by-step instructions will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. --
Author: Sas Education Publisher: ISBN: 9781642955880 Category : Computers Languages : en Pages : 126
Book Description
SAS Visual Data Mining and Machine Learning, powered by SAS Viya, means that users of all skill levels can visually explore data on their own while drawing on powerful in-memory technologies for faster analytic computations and discoveries. You can manually program with custom code or use the features in SAS Studio, Model Studio, and SAS Visual Analytics to automate your data manipulation and modeling. These programs offer a flexible, easy-to-use, self-service environment that can scale on an enterprise-wide level. In this book, we will explore some of the many features of SAS Visual Data Mining and Machine Learning including: programming in the Python interface; new, advanced data mining and machine learning procedures; pipeline building in Model Studio, and model building and comparison in SAS Visual Analytics.
Author: Tricia Aanderud Publisher: SAS Institute ISBN: 1635260442 Category : Computers Languages : en Pages : 294
Book Description
Focusing on the version of SAS Visual Analytics on SAS 9.4, this thorough guide will show you how to make sense of your complex data with the goal of leading you to smarter, data-driven decisions without having to write a single line of code ¿̐ư unless you want to. --
Author: Teresa Jade Publisher: SAS Institute ISBN: 1635266610 Category : Computers Languages : en Pages : 275
Book Description
Extract actionable insights from text and unstructured data. Information extraction is the task of automatically extracting structured information from unstructured or semi-structured text. SAS Text Analytics for Business Applications: Concept Rules for Information Extraction Models focuses on this key element of natural language processing (NLP) and provides real-world guidance on the effective application of text analytics. Using scenarios and data based on business cases across many different domains and industries, the book includes many helpful tips and best practices from SAS text analytics experts to ensure fast, valuable insight from your textual data. Written for a broad audience of beginning, intermediate, and advanced users of SAS text analytics products, including SAS Visual Text Analytics, SAS Contextual Analysis, and SAS Enterprise Content Categorization, this book provides a solid technical reference. You will learn the SAS information extraction toolkit, broaden your knowledge of rule-based methods, and answer new business questions. As your practical experience grows, this book will serve as a reference to deepen your expertise.
Author: Ken Kleinman Publisher: CRC Press ISBN: 1420070592 Category : Mathematics Languages : en Pages : 325
Book Description
An All-in-One Resource for Using SAS and R to Carry out Common TasksProvides a path between languages that is easier than reading complete documentationSAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, id
Author: Troy Martin Hughes
Author: Troy Martin Hughes
Author: Matthew Windham
Author: 
Author: Troy Martin Hughes
Author: Olivia Parr-Rud
Author: David Pope
Author: Sas Education
Author: Tricia Aanderud
Author: Teresa Jade
Author: Ken Kleinman