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Explore powerful SAS analytics and the Internet of Things!The world that we live in is more connected than ever before. The Internet of Things (IoT) consists of mechanical and electronic devices connected to one another and to software through the internet. Businesses can use the IoT to quickly make intelligent decisions based on massive amounts of data gathered in real time from these connected devices. IoT increases productivity, lowers operating costs, and provides insights into how businesses can serve existing markets and expand into new ones.Intelligence at the Edge: Using SAS with the Internet of Things is for anyone who wants to learn more about the rapidly changing field of IoT. Current practitioners explain how to apply SAS software and analytics to derive business value from the Internet of Things. The cornerstone of this endeavor is SAS Event Stream Processing, which enables you to process and analyze continuously flowing events in real time. With step-by-step guidance and real-world scenarios, you will learn how to apply analytics to streaming data. Each chapter explores a different aspect of IoT, including the analytics life cycle, monitoring, deployment, geofencing, machine learning, artificial intelligence, condition-based maintenance, computer vision, and edge devices.
The Global English Style Guide illustrates how much you can do to make written texts more suitable for a global audience. Accompanied by an abundance of clearly explained examples, the Global English guidelines show you how to write documentation that is optimized for non-native speakers of English, translators, and even machine-translation software, as well as for native speakers of English. You'll find dozens of guidelines that you won't find in any other source, along with thorough explanations of why each guideline is useful. Author John Kohl also includes revision strategies, as well as caveats that will help you avoid applying guidelines incorrectly.Focusing primarily on sentence-level stylistic issues, problematic grammatical constructions, and terminology issues, this book addresses the following topics: ways to simplify your writing style and make it consistent; ambiguities that most writers and editors are not aware of, and how to eliminate those ambiguities; how to make your sentence structure more explicit so that your sentences are easier for native and non-native speakers to read and understand; punctuation and capitalization guidelines that improve readability and make translation more efficient; and how language technologies such as controlled-authoring software canfacilitate the adoption of Global English as a corporate standard.This text is intended for anyone who uses written English to communicate technical information to a global audience. Technical writers, technical editors, science writers, and training instructors are just a few of the professions for which this book is essential reading. Even if producing technical information is not your primary job function, the Global English guidelines can help you communicate more effectively with colleagues around the world.
Edward Vonesh's Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS is devoted to the analysis of correlated response data using SAS, with special emphasis on applications that require the use of generalized linear models or generalized nonlinear models. Written in a clear, easy-to-understand manner, it provides applied statisticians with the necessary theory, tools, and understanding to conduct complex analyses of continuous and/or discrete correlated data in a longitudinal or clustered data setting. Using numerous and complex examples, the book emphasizes real-world applications where the underlying model requires a nonlinear rather than linear formulation and compares and contrasts the various estimation techniques for both marginal and mixed-effects models. The SAS procedures MIXED, GENMOD, GLIMMIX, and NLMIXED as well as user-specified macros will be used extensively in these applications. In addition, the book provides detailed software code with most examples so that readers can begin applying the various techniques immediately.
The SAS® Certified Specialist Prep Guide: Base Programming Using SAS® 9.4 prepares you to take the new SAS 9.4 Base Programming -- Performance-Based Exam. This is the official guide by the SAS Global Certification Program. This prep guide is for both new and experienced SAS users, and it covers all the objectives that are tested on the exam. New in this edition is a workbook whose sample scenarios require you to write code to solve problems and answer questions. Answers for the chapter quizzes and solutions for the sample scenarios in the workbook are included. You will also find links to exam objectives, practice exams, and other resources such as the Base SAS® glossary and a list of practice data sets. Major topics include importing data, creating and modifying SAS data sets, and identifying and correcting both data syntax and programming logic errors. All exam topics are covered in these chapters: Setting Up Practice Data Basic Concepts Accessing Your Data Creating SAS Data Sets Identifying and Correcting SAS Language Errors Creating Reports Understanding DATA Step Processing BY-Group Processing Creating and Managing Variables Combining SAS Data Sets Processing Data with DO Loops SAS Formats and Informats SAS Date, Time, and Datetime Values Using Functions to Manipulate Data Producing Descriptive Statistics Creating Output Practice Programming Scenarios (Workbook)
Create compelling business infographics with SAS and familiar office productivity tools. A picture is worth a thousand words, but what if there are a billion words? When analyzing big data, you need a picture that cuts through the noise. This is where infographics come in. Infographics are a representation of information in a graphic format designed to make the data easily understandable. With infographics, you don't need deep knowledge of the data. The infographic combines story telling with data and provides the user with an approachable entry point into business data. Infographics Powered by SAS: Data Visualization Techniques for Business Reporting shows you how to create graphics to communicate information and insight from big data in the boardroom and on social media. Learn how to create business infographics for all occasions with SAS and learn how to build a workflow that lets you get the most from your SAS system without having to code anything, unless you want to! This book combines the perfect blend of creative freedom and data governance that comes from leveraging the power of SAS and the familiarity of Microsoft Office. Topics covered in this book include: SAS Visual Analytics SAS Office Analytics SAS/GRAPH software (SAS code examples) Data visualization with SAS Creating reports with SAS Using reports and graphs from SAS to create business presentations Using SAS within Microsoft Office
Find errors and clean up data easily using SAS! Thoroughly updated, Cody's Data Cleaning Techniques Using SAS, Third Edition, addresses tasks that nearly every data analyst needs to do - that is, make sure that data errors are located and corrected. Written in Ron Cody's signature informal, tutorial style, this book develops and demonstrates data cleaning programs and macros that you can use as written or modify which will make your job of data cleaning easier, faster, and more efficient. Building on both the author's experience gained from teaching a data cleaning course for over 10 years, and advances in SAS, this third edition includes four new chapters, covering topics such as the use of Perl regular expressions for checking the format of character values (such as zip codes or email addresses) and how to standardize company names and addresses. With this book, you will learn how to: find and correct errors in character and numeric values develop programming techniques related to dates and missing values deal with highly skewed data develop techniques for correcting your data errors use integrity constraints and audit trails to prevent errors from being added to a clean data set
Access and clean up data easily using JMP(R)! Data acquisition and preparation commonly consume approximately 75% of the effort and time of total data analysis. JMP provides many visual, intuitive, and even innovative data-preparation capabilities that enable you to make the most of your organization's data. Preparing Data for Analysis with JMP is organized within a framework of statistical investigations and model-building and illustrates the new data-handling features in JMP, such as the Query Builder. Useful to students and programmers with little or no JMP experience, or those looking to learn the new data-management features and techniques, it uses a practical approach to getting started with plenty of examples. Using step-by-step demonstrations and screenshots, this book walks you through the most commonly used data-management techniques that also include lots of tips on how to avoid common problems. With this book, you will learn how to: Manage database operations using the JMP Query Builder Get data into JMP from other formats, such as Excel, csv, SAS, HTML, JSON, and the web Identify and avoid problems with the help of JMP's visual and automated data-exploration tools Consolidate data from multiple sources with Query Builder for tables Deal with common issues and repairs that include the following tasks: reshaping tables (stack/unstack) managing missing data with techniques such as imputation and Principal Components Analysis cleaning and correcting dirty data computing new variables transforming variables for modelling reconciling time and date Subset and filter your data Save data tables for exchange with other platforms
Strategies for Formulations Development: A Step-by-Step Guide Using JMP is based on the authors' significant practical experience partnering with scientists to develop strategies to accelerate the formulation (mixtures) development process. The authors not only explain the most important methods used to design and analyze formulation experiments, but they also present overall strategies to enhance both the efficiency and effectiveness of the development process. With this book you will be able to: Approach the development process from a strategic viewpoint with the overall end result in mind. Design screening experiments to identify components that are most important to the performance of the formulation. Design optimization experiments to identify the maximum response in the design space. Analyze both screening and optimization experiments using graphical and numerical methods. Optimize multiple criteria, such as the quality, cost, and performance of product formulations. Design and analyze formulation studies that involve both formulation components and process variables using methods that reduce the required experimentation by up to 50%. Linking dynamic graphics with powerful statistics, JMP helps construct a visually compelling narrative to interactively share findings that are coherent and actionable by colleagues and decision makers. Using this book, you can take advantage of computer generated experiment designs when classical designs do not suffice, given the physical and economic constraints of the experiential environment. Strategies for Formulations Development: A Step-by-Step Guide Using JMP(R) is unique because it provides formulation scientists with the essential information they need in order to successfully conduct formulation studies in the chemical, biotech, and pharmaceutical industries.
To illustrate the power and flexibility of SAS Viya, several groundbreaking papers have been carefully selected from recent SAS Global Forum presentations to introduce you to the topics and to let you sample what each has to offer. Also available for free as a PDF from sas.com/books.
SAS Visual Analytics is a business intelligence and analytics platform that provides visual exploration and discovery, self-service analytics, and interactive reporting for organizations of all sizes. All organizations have a wide variety of users, and each user needs something different from data and analytics. SAS Visual Analytics allows everyone to easily discover and share powerful insights that inspire action. Several useful 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.
Machine learning is a branch of artificial intelligence (AI) that develops algorithms that allow computers to learn from examples without being explicitly programmed. Machine learning identifies patterns in the data and models the results. These descriptive models enable a better understanding of the underlying insights the data offers. Machine learning is a powerful tool with many applications, from real-time fraud detection, the Internet of Things (IoT), recommender systems, and smart cars. It will not be long before some form of machine learning is integrated into all machines, augmenting the user experience and automatically running many processes intelligently. SAS offers many different solutions to use machine learning to model and predict your data. The papers included in this special collection demonstrate how cutting-edge machine learning techniques can benefit your data analysis. Also available free as a PDF from sas.com/books.
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