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Expert T-SQL Window Functions in SQL Server

Expert T-SQL Window Functions in SQL Server takes you from any level of knowledge of windowing functions and turns you into an expert who can use these powerful functions to solve many T-SQL queries. Replace slow cursors and self-joins with queries that are easy to write and fantastically better performing, all through the magic of window functions. First introduced in SQL Server 2005, window functions came into full blossom with SQL Server 2012. They truly are one of the most notable developments in SQL in a decade, and every developer and DBA can benefit from their expressive power in solving day-to-day business problems. Begin using windowing functions like ROW_NUMBER and LAG, and you will discover more ways to use them every day. You will approach SQL Server queries in a different way, thinking about sets of data instead of individual rows. Your queries will run faster, they will be easier to write, and they will be easier to deconstruct and maintain and enhance in the future. Just knowing and using these functions is not enough. You also need to understand how to tune the queries. Expert T-SQL Window Functions in SQL Server explains clearly how to get the best performance. The book also covers the rare cases when older techniques are the best bet. Stop using cursors and self-joins to solve complicated queries. Become a T-SQL expert by mastering windowing functions.Teaches you how to use all the window functions introduced in 2005 and 2012.Provides real-world examples that you can experiment with in your own database. Explains how to get the best performance when using windowing functions.

Expert T-SQL Window Functions in SQL Server 2019: The Hidden Secret to Fast Analytic and Reporting Queries

Become an expert who can use window functions to solve T-SQL query problems. Replace slow cursors and self-joins with queries that are easy to write and perform better. This new edition provides expanded examples, including a chapter from the world of sports, and covers the latest performance enhancements through SQL Server 2019. Window functions are useful in analytics and business intelligence reporting. They came into full blossom with SQL Server 2012, yet they are not as well known and used as often as they ought to be. This group of functions is one of the most notable developments in SQL, and this book shows how every developer and DBA can benefit from their expressive power in solving day-to-day business problems. Once you begin using window functions, such as ROW_NUMBER and LAG, you will discover many ways to use them. You will approach SQL Server queries in a different way, thinking about sets of data instead of individual rows. Your queries will run faster, be easier to write, and easier to deconstruct, maintain, and enhance in the future.Just knowing and using these functions is not enough. You also need to understand how to tune the queries. Expert T-SQL Window Functions in SQL Server clearly explains how to get the best performance. The book also covers the rare cases when older techniques are the best bet.What You Will LearnSolve complex query problems without cumbersome self-joins that run slowly and are difficult to readCreate sliding windows in a result set for computing such as running totals and moving averagesReturn aggregate and detail data simultaneously from the same SELECT statementCompute lag and lead and other values that access data from multiple rows in a result setUnderstand the OVER clause syntax and how to control the windowAvoid framing errors that can lead to unexpected resultsWho This Book Is For Anyone who writes T-SQL queries, including database administrators, developers, business analysts, and data scientists. Before reading this book, you should understand how to join tables, write WHERE clauses, and build aggregate queries.

Expert Twisted: Event-driven And Asynchronous Programming With Python

Explore Twisted, the Python-based event-driven networking engine, and review several of its most popular application projects. It is written by community leaders who have contributed to many of the projects covered, and share their hard-won insights and experience.Expert Twisted starts with an introduction to event-driven programming, explaining it in the context of what makes Twisted unique. It shows how Twisted's design emphasizes testability as a solution to common challenges of reliability, debugging, and start-to-finish causality that are inherent in event-driven programming. It also explains asynchronous programming, and the importance of functions, deferreds, and coroutines. It then uses two popular applications, treq and klein, to demonstrate calling and writing Web APIs with Twisted.The second part of the book dives into Twisted projects, in each case explaining how the project fits into the Twisted ecosystem and what it does, and offers several examples to bring readers up to speed, with pointers to additional resources for more depth. Examples include using Twisted with Docker, as a WSGI container, for file sharing, and more.What You'll LearnIntegrate Twisted and asyncio using adaptersAutomate software build, test, and release processes with BuildbotCreate clients and servers with AutobahnTransfer files with Magic WormholeDistribute cloud-based file storage with Tahoe LAFSUnderstand HTTP/2 with Python and TwistedSupport for asynchronous tasks using Django ChannelsWho This Book Is ForReaders should have some Python experience and understand the essentials of containers and protocols, but need not be familiar with Twisted or the associated projects covered in the book.

Expert VB 2005 Business Objects

Popular conference speaker "Rocky" Lhotka shows how to use the framework to create a sample application and demonstrates how easy it is to write Windows, Web, and Web services interfaces for applications based on it.

Expert VB 2008 Business Objects

Do you want to create .NET applications that provide high performance and scalability? Do you want to employ object–oriented programming techniques in a distributed environment? Do you want to maximize the reuse and maintainability of your code? Then this book is for you. In Rockford Lhotka's Expert VB 2008 Business Objects, you'll learn how to use advanced .NET Framework capabilities alongside object-oriented design and programming to create scalable, maintainable object–oriented applications. Better still, this book includes Component-based Scalable Logical Architecture (CSLA) .NET 3.6, a widely-used framework on which you can base your application development. By using the concepts and framework in the book, you can focus more on your business issues, and less on technology. Having updated this third edition using Visual Studio 2008 and Visual Basic 2008, Rockford Lhotka shows you how CSLA .NET 3.6 allows great flexibility in object persistence, so business objects can use virtually any data sources available. The CSLA framework supports 1–, 2–, and n–tier models through the concept of mobile objects. This provides the flexibility to optimize performance, scalability, security, and fault tolerance with no changes to code in the user interface or business objects. Business objects based on CSLA .NET 3.6 automatically gain many advanced features that simplify the creation of Windows forms, web forms, WPF, WCF, WF and Web Services interfaces, and LINQ.

Expert Visual C++/CLI: .NET for Visual C++ Programmers

Stan Lippman is one of the best-selling authors on C++ and has long been one of the major contributors to its growth and standardization. Written by experts, and full of sound expert insight and advice, this book can be read profitably by any C++ programmer. Short code examples concisely illustrate concepts, and more elaborate examples show how C++/CLI is best used. Even programmers new to C++/CLI, but planning to migrate to it from another language, can use this book to understand core language elements crucial to planning and migrating effectively.

Expertensystem-Praktikum (Springer Compass)

Schwimmen lernt man beim Schwimmen. Programmieren beim Programmieren. Und Expertensysteme zu schreiben beim Schreiben von Expertensystemen. Deshalb entstand dieses Buch: aus einem Expertensystem-Praktikum, das Soft­ ware-Praktiker in die neuen Entwurfs-und Programmiertechniken einführt, welche die wissensbasierte Datenverarbeitung in die Softwaretechnologie einbrachte. Dabei wird bewußt die Programmierung betont, nicht die Generierung eines Expertensy­ stems durch "Einfüllen" von Fachwissen in eine Shell. Was natürlich nicht heißen soll, daß sich nicht auch der Programmierer eines Expertensystems die eine oder andere Aufgabe erleichtern kann, indem er ein derartiges Metasystem als "Werk­ zeug" benutzt. Aber auch dann - das ist jedenfalls die Erfahrung der Autoren - können gute, benutzerfreundliche und leicht in die bereits vorhandenen konventionellen Daten­ basen und Anwendungen integrierbare Expertensysteme nur entstehen, wenn der Entwickler problemlos sich all die Komponenten selbst programmieren kann, die er in seinem vorgefertigten Werkzeugkasten überhaupt nicht, nicht in geeigneter Form oder nicht mit den richtigen Schnittstellen vorfindet. Im traditionellen Maschinenbau ist der "Werkzeugmacher" der gesuchteste und höchstbezahlte Fachspezialist. In unserem Handwerk ist das nicht viel anders.

Expertensysteme (Springers Angewandte Informatik)

Das vorliegende Buch gibt einen umfassenden Überblick über das wohl aktivste Forschungs- und Anwendungsgebiet der Artificial Intelligence - über Expertensysteme. Basierend auf den Erfahrungen aus mehrjähriger Vorlesungstätigkeit stellt das Autorenteam neben grundlegenden Konzepten auch die theoretischen wie praktischen Aspekte ausführlich dar. Eine kompetente Einführung in die Prädikatenlogik wird gegeben. Als Novum verdeutlicht dieses Buch die unterschiedlichen Schlußweisen und Komponenten von Expertensystemen durch ausführbare Prototypen in der logischen Programmiersprache Prolog. Dem praktischen Aspekt wird weiters durch einen Überblick über im industriellen Einsatz stehende Expertensysteme Rechnung getragen. Nicht zuletzt behandelt dieses Buch die neuesten Entwicklungen, wie Experten-Datenbanksysteme und Ergonomie und Gestaltung von Benutzerschnittstellen für Expertensysteme. Das Buch eignet sich damit nicht nur als Unterlage und Referenz für Vorlesungen auf dem Gebiet der Expertensysteme, vielmehr wendet es sich auch an den interessierten Informatiker und Programmierer in Studium und Praxis.

Expertensysteme: Nicht nur für Informatiker (Springer Compass)

Ein Weiser gibt nicht die richtigen Antworten. Er stellt die richtigen Fragen. Claude Levi-Strauss, Anthropologe Dieses Buch heißt "Expertensysteme" mit dem Untertitel "Nicht nur für Informatiker". Wir wollen damit auf zwei Punkte aufmerksam machen, auf die wir Wert legen. Erstens: Wir haben uns bemüht, zwar ein Fachbuch zu schreiben, aber kein Informa­ tik-Fachbuch. Wir wünschen uns, daß es ein Buch geworden ist, das auch derjenige mit Gewinn lesen kann, der nicht Informatik studiert hat und nicht Programmieren kann. Sondern der sich aus beruflichen Gründen, aus Neigung oder vielleicht auch aus einem Gefühl des Mißbehagens dafür interessiert, was denn da mit dieser "Künstlichen Intelli­ genz" auf uns zukommt. Zweitens: Wir sind aber der Meinung, daß dies besonders für Manager zutrifft. Ma­ nager sind die vielleicht wichtigsten Konsumenten von Expertenwissen. Denn eine ihrer Hauptaufgaben ist, dieses Wissen von Experten in Entscheidungen umzusetzen. Also werden Manager sich zunehmend auch mit Expertensystemen auseinanderset­ zen müssen. Und zwar in vielerlei Weise. - Sie können selbst Expertensysteme zur Entscheidungsvorbereitung nutzen. - Sie können Ihren Experten Expertensysteme ebenso als Hilfsmittel zur Verfügung stellen, wie ihren Buchhaltern Rechenmaschinen und ihren Sekretärinnen Textverar­ beitungssysteme. - Sie müssen gelegentlich zwischen verschiedenen Expertisen wählen (wobei zuweilen sogar als besonderes Qualitätsmerkmal einer Ansicht betont wird, sie stamme aus ei­ nem Computer). - Sie müssen vielleicht entscheiden, ob und wo es sich lohnt, Expertensysteme als Ent­ scheidungshilfen zu entwickeln - als Erweiterung und Ergänzung ihrer bestehenden Datenverarbeitung oder auch als vermarktbares Produkt, als eine unter den vielen Möglichkeiten, Fachkenntnisse verkaufbar zu machen.

Expertensysteme: Nicht nur für Informatiker (Springer Compass)

In der vorliegenden 2. Auflage dieser erfolgreichen Einführung in Expertensysteme wurden Fehler korrigiert und einige Aktualisierungen vorgenommen. Das Buch ist nach wie vor einzigartig und hochaktuell, da es ein vielseitiges Forschungs- und Anwendungsgebiet leicht verständlich und fesselnd darstellt.

Expertensysteme: Entscheidungsgrundlage für das Management

Expertensysteme 93: 2. Deutsche Tagung Expertensysteme (XPS-93) Hamburg, 17.–19. Februar 1993 (Informatik aktuell)

Expertensysteme für den Einsatz von Subroutinenpaketen: Am Beispiel eines Expertensystems für Bildverarbeitung

In dieser Arbeit wird ein Expertensystem vorgestellt, das einen Benutzer beim Einsatz der Bildverarbeitungssoftware SPIDER unterstützt. Ferner wird allgemein erläutert, wie Expertensysteme zur Kontrolle des Einsatzes von Subroutinenpaketen verwendet werden können. Es wird eine Expertensystem-Schale vorgestellt, welche das Erstellen von solchen Expertensystemen vereinheitlicht und vereinfacht. Vorwort zur Originaldissertation Zum Gelingen der vorliegenden Dissertation haben verschiedene Leute auf die eine oder andere Art beigetragen. An erster Stelle möchte ich Herrn Prof. Dr. H. Bunke für die Leitung dieser Arbeit danken. Von ihm stammt die Idee zur Entwicklung eines Exper­ tensystems für das Subroutinenpaket SPIDER. Er hat mir in vielen Gesprächen zahl­ reiche Anregungen gegeben und Hinweise auf relevante Literatur vermittelt. Auch hat er sich die Mühe genommen, die Entwürfe zur vorliegenden Arbeit durchzulesen und zu kommentieren. Der Firma Nixdorf Computer AG Schweiz danke ich für die Zurverfügungstellung der verwendeten Hardware (Computersystem Targon 131 mit Peripherie) und Software (TWAICE, IF/Prolog, UNIX, usw.). Ganz besonders möchte ich den Herren Dr. M. Grosser und W. Sonderegger danken, die meine Kontaktpersonen waren und meine Fragen und Probleme stets wohlwollend entgegennahmen und an die entsprechenden Spezialisten weiterleiteten. Dank gebührt auch Herrn R. Schreier (Elektrowatt Bern), auf dessen Vermittlung hin ein erster Kontakt zu Nixdorf zustande kam.

Expertensysteme in CIM (CIM-Fachmann)

Expertensysteme in Produktion und Engineering: IAO-Forum 25. April 1990 in Stuttgart (IPA-IAO - Forschung und Praxis Tagungsberichte #16)

Betrachtet man das ansteigende Interesse an einer neuen Technologie als Indikator für ihre Position im Markt, so zeichnen sich insbesondere Entwicklungen auf dem Gebiet der Expertensysteme durch einen stürmischen Zuwachs aus. Leider wird das oft in Forschungslabors erarbeitete Wissen in die praktische industrielle Anwendung nicht ebenso schnell transferiert. Um dem abzuhelfen, veranstaltete das IAO sein zweites Forum zu diesem Thema. Es zeigte hierbei vorrangig, daß anwendungsnahe Projekte mit realistischen Zielsetzungen durchaus zum erfolgreichen Einsatz gebracht werden können, wenn einige Randbedingungen berücksichtigt werden. Die zentrale, übergreifende Thematik dieses Forums, das als konsequente Fortsetzung der letzten Veranstaltung zu sehen ist, lag dieses Mal in einer integrierten Betrachtungsweise von Expertensystemen. Nur unter Berücksichtigung von akzeptierten Standards, nur unter Einbindung von Datenbanksystemen und Netzwerktechnologien und nur auf der Basis von marktgängigen Hardwareplattformen können Entwicklungen von wissensbasierten Systemen zu einem erfolgreichen Ende geführt werden.

Expertensysteme in Produktion und Engineering: IAO-Forum 24. April 1991 (IPA-IAO - Forschung und Praxis Tagungsberichte #23)

Expertise and Decision Support

This volume brings together a range of contributors from Europe and North America. All contributions were especially commissioned with a view to e- cidating a major multidisciplinary topic that is of concern to both academics and practitioners. The focus of the book is on expert judgment and its interaction with decision support systems. In the first part, the nature of expertise is discussed and characteristics of expert judges are described. Issues concemed with the eval- tion of judgment in the psychological laboratory are assessed and contrasted with studies of expert judgment in ecologically valid contexts. In addition, issues concerned with eliciting and validating expert knowledge are discussed. Dem- strations of good judgmental performance are linked to situational factors such as feedback cycles, and measurement of coherence and reliability in expert ju- ment is introduced as a baseline determinant of good judgmental performance. Issues concerned with the representation of elicited expert knowledge in kno- edge-based systems are evaluated and methods are described that have been shown to produce improvements in judgmental performance. Behavioral and mathematical ways of combining judgments from multiple experts are compared and contrasted. Finally, the issues developed in the preceding contributions are focused on current controversies in decision support. Expert judgment is utilized as a major input into decision analysis, forecasting with statistical models, and expert s- tems.

Expertise at Work: Current and Emerging Trends

Expertise, which combines knowledge, years of experience in one domain, problem-solving skills, and behavioral traits, is a valuable resource for organizations. To understand the diverse picture of expertise in the workplace, this book offers scholars and scholar-practitioners a comprehensive assessment of the development of human expertise in organizations. Using contemporary perspectives across a broad range of domains, contributors offer readers various professional perspectives including veterans, education, sports, and information technology. The book also describes how researchers and practitioners can address practical problems related to the development, redevelopment, and sustainability of expertise. Finally, the book puts specific emphasis on the emerging trends in the study and practice of expertise in organizations, including the use of artificial intelligence.

Explainable Agency in Artificial Intelligence: Research and Practice (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

This book focuses on a subtopic of explainable AI (XAI) called explainable agency (EA), which involves producing records of decisions made during an agent’s reasoning, summarizing its behavior in human-accessible terms, and providing answers to questions about specific choices and the reasons for them. We distinguish explainable agency from interpretable machine learning (IML), another branch of XAI that focuses on providing insight (typically, for an ML expert) concerning a learned model and its decisions. In contrast, explainable agency typically involves a broader set of AI-enabled techniques, systems, and stakeholders (e.g., end users), where the explanations provided by EA agents are best evaluated in the context of human subject studies. The chapters of this book explore the concept of endowing intelligent agents with explainable agency, which is crucial for agents to be trusted by humans in critical domains such as finance, self-driving vehicles, and military operations. This book presents the work of researchers from a variety of perspectives and describes challenges, recent research results, lessons learned from applications, and recommendations for future research directions in EA. The historical perspectives of explainable agency and the importance of interactivity in explainable systems are also discussed. Ultimately, this book aims to contribute to the successful partnership between humans and AI systems. Features: • Contributes to the topic of explainable artificial intelligence (XAI) • Focuses on the XAI subtopic of explainable agency • Includes an introductory chapter, a survey, and five other original contributions

Explainable Agency in Artificial Intelligence: Research and Practice (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

This book focuses on a subtopic of explainable AI (XAI) called explainable agency (EA), which involves producing records of decisions made during an agent’s reasoning, summarizing its behavior in human-accessible terms, and providing answers to questions about specific choices and the reasons for them. We distinguish explainable agency from interpretable machine learning (IML), another branch of XAI that focuses on providing insight (typically, for an ML expert) concerning a learned model and its decisions. In contrast, explainable agency typically involves a broader set of AI-enabled techniques, systems, and stakeholders (e.g., end users), where the explanations provided by EA agents are best evaluated in the context of human subject studies. The chapters of this book explore the concept of endowing intelligent agents with explainable agency, which is crucial for agents to be trusted by humans in critical domains such as finance, self-driving vehicles, and military operations. This book presents the work of researchers from a variety of perspectives and describes challenges, recent research results, lessons learned from applications, and recommendations for future research directions in EA. The historical perspectives of explainable agency and the importance of interactivity in explainable systems are also discussed. Ultimately, this book aims to contribute to the successful partnership between humans and AI systems. Features: • Contributes to the topic of explainable artificial intelligence (XAI) • Focuses on the XAI subtopic of explainable agency • Includes an introductory chapter, a survey, and five other original contributions

Explainable AI and Other Applications of Fuzzy Techniques: Proceedings of the 2021 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2021 (Lecture Notes in Networks and Systems #258)

This book focuses on an overview of the AI techniques, their foundations, their applications, and remaining challenges and open problems. Many artificial intelligence (AI) techniques do not explain their recommendations. Providing natural-language explanations for numerical AI recommendations is one of the main challenges of modern AI. To provide such explanations, a natural idea is to use techniques specifically designed to relate numerical recommendations and natural-language descriptions, namely fuzzy techniques. This book is of interest to practitioners who want to use fuzzy techniques to make AI applications explainable, to researchers who may want to extend the ideas from these papers to new application areas, and to graduate students who are interested in the state-of-the-art of fuzzy techniques and of explainable AI—in short, to anyone who is interested in problems involving fuzziness and AI in general.

Explainable AI for Cybersecurity

This book provides a comprehensive overview of security vulnerabilities and state-of-the-art countermeasures using explainable artificial intelligence (AI). Specifically, it describes how explainable AI can be effectively used for detection and mitigation of hardware vulnerabilities (e.g., hardware Trojans) as well as software attacks (e.g., malware and ransomware). It provides insights into the security threats towards machine learning models and presents effective countermeasures. It also explores hardware acceleration of explainable AI algorithms. The reader will be able to comprehend a complete picture of cybersecurity challenges and how to detect them using explainable AI. This book serves as a single source of reference for students, researchers, engineers, and practitioners for designing secure and trustworthy systems.

Explainable AI: Foundations, Methodologies and Applications (Intelligent Systems Reference Library #232)

This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.

Explainable AI in Health Informatics (Computational Intelligence Methods and Applications)

This book provides a comprehensive review of the latest research in the area of explainable artificial intelligence (XAI) in health informatics. It focuses on how explainable AI models can work together with humans to assist them in decision-making, leading to improved diagnosis and prognosis in healthcare. This book includes a collection of techniques and systems of XAI in health informatics and gives a wider perspective about the impact created by them. The book covers the different aspects, such as robotics, informatics, drugs, patients, etc., related to XAI in healthcare. The book is suitable for both beginners and advanced AI practitioners, including students, academicians, researchers, and industry professionals. It serves as an excellent reference for undergraduate and graduate-level courses on AI for medicine/healthcare or XAI for medicine/healthcare. Medical institutions can also utilize this book as reference material and provide tutorials to medical professionals on how the XAI techniques can contribute to trustworthy diagnosis and prediction of the diseases.

Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine (Analytics and AI for Healthcare)

This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering. This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care