Provides a resource for use if any problems are encountered during an initial installation.

Explains how to administer the SAS Web applications that run in the middle tier of the SAS Intelligence Platform. The Web applications include the SAS Information Delivery Portal, SAS Web Report Studio, and SAS Web OLAP Viewer for Java.This guide describes the middle-tier environment, provides sample deployment scenarios, and explains how to configure the Web applications for optimal performance. The guide contains instructions for common administrative tasks, such as configuring trusted Web authentication, as well as instructions for administering the individual Web applications. For example, the guide explains how to add content to the SAS Information Delivery Portal and how to control access to that content. This title is also available online.

The current rapid development in both computing power and the ability to present and mine complex data sets in useful ways provides the backdrop to Intelligence Management: Knowledge Driven Frameworks for Combating Terrorism and Organized Crime. The chapters address the linkage between: law enforcement; developments in information and communication technologies and key ideas about the management of data, information, knowledge and intelligence. The work is conducted by a number of international academic and industrial research groups, law enforcement agencies, and end users. Section 1 presents four chapters that address the details, outcomes, user needs and background theoretical ideas behind a large-scale research aand development project in this domain (The Odyssey Project). This project explored the challenges of establishing a Pan-European ballistics and crime information intelligence network. It represents an example of the type of system that is likely to become commonly used by Law Enforcement Agencies in the near future. Many of the challenges are not technical but organisational, legal, economic, social and political. Sections 2 and 3 therefore present wider commentaries. Section 2 explores other research and development projects that attempt to exploit the power of contemporary ICT systems to support Law Enforcement Agencies in many aspects of their work including investigations, data analysis and presentation, identification, training and crime prevention. Section 3 takes a look at the social and organisational issues around aspects of crime prevention, crime detection and policing – with a view to the role of information and communication technologies in these contexts.

Customize the SAS Stored Process web application to create amazing tools for end users. This book shows you how to use stored processes—SAS programs stored on a server and executed as required by requesting applications. Never before have there been so many ways to turn data into information and build applications with SAS. This book teaches you how to use the web technologies that you frequently see used on impressive websites. By using SAS Stored Processes, you will be able to build applications that exploit CSS, JavaScript, and HTML libraries and enable you to build powerful and impressive web applications using SAS as the backend. While this approach is not common with SAS users, some have had amazing results. People who have SAS skills usually do not have web development skills, and those with web development skills usually do not have SAS skills. Some people have both skills but are unaware of how to connect them with the SAS Stored Process web application. This book shows you how to leverage your skills for success. What You Will Learn Know the benefits of stored processesWrite your own tools in SASMake a stored process generate its own HTML menuPass data between stored processesUse stored processes to generate pure JavaScriptUtilize data generated by SASConvert a SAS program into a stored process Who This Book Is For SAS programmers looking to improve their existing programming skills to develop web applications, and programming managers who want to make better use of the SAS software they already license

A straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the "need-to-know" aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way. Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. Straightforward, pragmatic, and with no math required, this book will help you: Speak intelligently about Artificial Intelligence and its advantages in marketing Understand how marketers without a Data Science degree can make use of machine learning technology Collaborate with data scientists as a subject matter expert to help develop focused-use applications Help your company gain a competitive advantage by leveraging leading-edge technology in marketing Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve.

A comprehensive index to company and industry information in business journals.

Explains the source and content of administrative healthcare data, which is the product of financial reimbursement for healthcare services. The book integrates the business knowledge of healthcare data with practical and pertinent case studies as shown in SAS Enterprise Guide.

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

Tracking originated with man’s need for food; he needed to understand what he was following and what the rewards would be if he was successful. Little has changed over time about the terms of tracking. We still track game for sport and food, but we have also found other uses for tracking. Border police patrol to stop illegal immigrants from entering their country; the military tracks down wanted terrorists or enemy forces. Tracking has become a military skill. In the SAS Tracking Handbook, former SAS soldier and British Empire Medal (BEM) award–winner Barry Davies teaches not only how to survive in the outdoors with the skills of tracking, but how to use these skills from a military standpoint. Included in this book are many helpful tips on topics including: The types of dogs used for tracking. Traps for catching wild animals. Modern military tracking. Using your surroundings to your advantage. And much more. The success or failure of the modern tracker is dependent on the personal skills of the individual tracker. Training is vital in learning tracking skills, and continuous exercise the best way to interpret signs. These skills are rarely found, but they remain hidden deep within all of us. So whether you’re already a skilled tracker or a novice in the field, the SAS Tracking Handbook will be your guide to mastering this old and respected art.

This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.