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DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field. This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library. Deep Learning Approaches to Cloud Security: Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas

This book presents a framework for developing an analytics strategy that includes a range of activities, from problem definition and data collection to data warehousing, analysis, and decision making. The authors examine best practices in team analytics strategies such as player evaluation, game strategy, and training and performance. They also explore the way in which organizations can use analytics to drive additional revenue and operate more efficiently. The authors provide keys to building and organizing a decision intelligence analytics that delivers insights into all parts of an organization. The book examines the criteria and tools for evaluating and selecting decision intelligence analytics technologies and the applicability of strategies for fostering a culture that prioritizes data-driven decision making. Each chapter is carefully segmented to enable the reader to gain knowledge in business intelligence, decision making and artificial intelligence in a strategic management context.

This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, this book emphasizes the process of asking relevant questions to inform public policy. Its techniques and approaches emphasize data-driven practices, beginning with the basic programming paradigms that occupy the majority of an analyst's time and advancing to the practical applications of statistical learning and machine learning. The text considers two divergent, competing perspectives to support its applications, incorporating techniques from both causal inference and prediction. Additionally, the book includes open-sourced data as well as live code, written in R and presented in notebook form, which readers can use and modify to practice working with data.

This book focuses on big data in business intelligence, data management, machine learning, cloud computing, and smart cities. It also provides an interdisciplinary platform to present and discuss recent innovations, trends, and concerns in the fields of big data and analytics.Big Data Analysis for Green Computing: Concepts and Applications presents the latest technologies and covers the major challenges, issues, and advances of big data and data analytics in green computing. It explores basic as well as high-level concepts. It also includes the use of machine learning using big data and discusses advanced system implementation for smart cities.The book is intended for business and management educators, management researchers, doctoral scholars, university professors, policymakers, and higher academic research organizations.

This book asks a simple question: are the tech giants monopolies? In the current environment of suspicion towards the major technology companies as a result of concerns about their power and influence, it has become commonplace to talk of Google, Facebook, Amazon, Apple, Microsoft, or Netflix as the modern day version of the 19th century trusts. In turn, the tech giants are vilified for a whole range of monopoly harms towards consumers, workers and even the democratic process. In the US and the EU, antitrust, and regulatory reform is on the way. Using economics, business and management science as well legal reasoning, this book offers a new perspective on big tech. It builds a theory of'moligopoly'. The theory advances that the tech giants, or at least some of them, coexist both as monopolies and oligopoly firms that compete against each other in an environment of substantial uncertainty and economic dynamism. With this, the book assesses ongoing antitrust and regulatory policy efforts. It demonstrates that it is counterproductive to pursue policies that introduce more rivalry in moligopoly markets subject to technological discontinuities. And that non-economic harms like privacy violations, fake news, or hate speech are difficult issues that belong to the realm of regulation, not antimonopoly remediation.

Masterarbeit aus dem Jahr 2018 im Fachbereich BWL - Unternehmensführung, Management, Organisation, Note: 1,3, FOM Hochschule für Oekonomie & Management gemeinnützige GmbH, Stuttgart, Sprache: Deutsch, Abstract: Der Autor beantwortet zentrale Fragen für den Einsatz von Business Intelligence in der Gastronomie Fahre ich heute mit dem Auto oder mit dem Fahrrad zur Arbeit? Welche Speisen nehme ich nächste Woche für meine Kunden auf die Mittagskarte? Investiere ich in die online-Kampagne oder lieber in Flyer? Ständig werden von Menschen Entscheidungen getroffen. Oft kommt dabei die Intuition zum Einsatz, die trotz fehlender oder unvollständiger Informationslage durch den Einsatz von Heuristiken zu schnellen Ergebnissen kommt. Der Nachteil von Heuristiken ist die Fehleranfälligkeit, die zu schlechteren Entscheidungen führen kann. Wie in allen Unternehmen, ist in der Gastronomie das Treffen von Entscheidungen von zentraler Bedeutung. Daher ist es erstrebenswert, den Einsatz von Heuristiken bei der Entscheidungsfindung möglichst zu reduzieren. Eine Möglichkeit dafür ist, zum Entscheidungszeitpunkt eine ausreichend große Menge handlungsrelevanter Informationen bereitzustellen. Der Weg dorthin lässt sich auch als Übergang vom Schätzen hin zu besseren Entscheidungen durch Wissen beschreiben. Während in vielen Branchen dieser Wandel mit Hilfe von Business Intelligence bereits vollzogen wird, ist dies in der Gastronomie nicht zu beobachten. Mit dieser Arbeit soll dieser Wandel auch in der Gastronomie angestoßen werden. Gastronomen finden in dieser Arbeit eine praxisbezogene Grundlage, um die Basis ihrer eigenen Entscheidungen maßgeblich zu verbessern und sich so einen Wettbewerbsvorteil zu erarbeiten.

Der Bedeutungswandel des Marketings wurde spätestens mit dem Einzug der Digitalisierung spürbar: durch die Reduktion auf Verkaufszahlen und Kommunikation hat es sich selbst fast überflüssig gemacht. Marketing braucht Erneuerung und Rückbesinnung zugleich. Die Zukunft des Marketings liegt im Kristallisationspunkt aller unternehmerischer Tätigkeiten – dem radikalen Fokus auf den Kunden. Während viele Marketing-Ratgeber mit dem Appell „Zurück zum Kunden“ enden, zeigen die Autoren hier im Detail, warum Marketing ein neues Mindset braucht, wie es sich strategisch neu aufstellen und operativ zum Wohle des Kunden umsetzen lässt: empathisch, agil, ganzheitlich vernetzt und iterativ. Seriöses Marketing kann so bei der Lösung wirklich drängender, menschlicher Probleme helfen. Die Autoren analysieren messerscharf die vernachlässigte Marketing-Kultur in vielen B2C- und B2B-Unternehmen. Mit dem von ihnen entwickelten H2H-(Human-to-Human)-Marketing-Konzept weisen sie den Weg füreine radikale Neuorientierung im Marketing. Sie präsentieren keine markigen Sprüche, coolen Buzzwords oder romantischen Fantasien, sondern professionelles Handwerk, das Marketing-Profis für ihre tägliche Arbeit beherrschen müssen. Marketing wird so wieder respektiert werden, muss sich dies aber durch neues Wissen und verbesserte Fähigkeiten zunächst verdienen. Aus dem InhaltDer notwendige Wandel im Marketing Mindset durch Design Thinking, Service-Dominant-Logic und Digitalisierung. Vertrauen und dessen Management in Form von Marke, Customer Experience und Reputation wird in der Praxis häufig unterschätzt und ist doch so wirksam. Der konkrete Weg zum H2H-Marketing mit Prozess und Instrumenten. So erzeugen Sie echte Mitarbeiter- und Kundenbegeisterung.

Der Band erarbeitet theoretisch, empirisch, method(olog)isch und praxisorientiert Zugänge zum Verhältnis von Organisation und Netzwerken und untersucht die Verbindung zwischen sozialer Netzwerkforschung und erziehungswissenschaftlicher/ organisationspädagogischer Diskussion. Der InhaltTheorie und Methodologie in der Netzwerk- und Organisationsforschung • Organisationales Lernen und Steuerung in und von Netzwerken • Vernetzung, soziale Dienstleistungsorganisationen und Adressat•innen • Netzwerkförmige und digitale Arbeits- und Organisationsformen • Netzwerke und Schule(n) • Netzwerke, Hochschule und InnovationDie HerausgeberInnenDr. Susanne Maria Weber ist Professorin am Institut für Erziehungswissenschaft an der Philipps-Universität Marburg.Dr. Inga Truschkat ist Professorin am Institut für Sozial- und Organisationspädagogik an der Universität Hildesheim.Dr. Christian Schröder ist wissenschaftlicher Mitarbeiter (Post-Doc) an der Fakultät für Sozialwissenschaften an der Hochschule für Technik und Wirtschaft des Saarlandes.Luisa Peters ist wissenschaftliche Mitarbeiterin am Institut für Sozial- und Organisationspädagogik an der Universität Hildesheim.Dr. Andreas Herz ist wissenschaftlicher Mitarbeiter (Post-Doc) am Institut für Sozial- und Organisationspädagogik an der Universität Hildesheim.

Assistive technologies for the old and people with disabilities is now a very active field of research. It also constitutes a very profitable market (expected to reach US $60 billion p.a. by 2018). The book covers key aspects of this important field and provides guidelines for developing assistive technologies in smart environments. The book also presents the new paradigm of open innovation used by the most prolific research teams around the world. The latest developments in the field are given. Overall this book will be a reference for researchers, practitioners and engineers.

The SAGE Handbook of Social Media Research Methods offers a step-by-step guide to overcoming the challenges inherent in research projects that deal with ‘big and broad data', from the formulation of research questions through to the interpretation of findings. The handbook includes chapters on specific social media platforms such as Twitter, Sina Weibo and Instagram, as well as a series of critical chapters. The holistic approach is organised into the following sections: Conceptualising & Designing Social Media Research Collection & Storage Qualitative Approaches to Social Media Data Quantitative Approaches to Social Media Data Diverse Approaches to Social Media Data Analytical Tools Social Media Platforms This handbook is the single most comprehensive resource for any scholar or graduate student embarking on a social media project.

Managing the Web of Things: Linking the Real World to the Web presents a consolidated and holistic coverage of engineering, management, and analytics of the Internet of Things. The web has gone through many transformations, from traditional linking and sharing of computers and documents (i.e., Web of Data), to the current connection of people (i.e., Web of People), and to the emerging connection of billions of physical objects (i.e., Web of Things). With increasing numbers of electronic devices and systems providing different services to people, Web of Things applications present numerous challenges to research institutions, companies, governments, international organizations, and others. This book compiles the newest developments and advances in the area of the Web of Things, ranging from modeling, searching, and data analytics, to software building, applications, and social impact. Its coverage will enable effective exploration, understanding, assessment, comparison, and the selection of WoT models, languages, techniques, platforms, and tools. Readers will gain an up-to-date understanding of the Web of Things systems that accelerates their research. Offers a comprehensive and systematic presentation of the methodologies, technologies, and applications that enable efficient and effective management of the Internet of Things Provides an in-depth analysis on the state-of-the-art Web of Things modeling and searching technologies, including how to collect, clean, and analyze data generated by the Web of Things Covers system design and software building principles, with discussions and explorations of social impact for the Web of Things through real-world applications Acts as an ideal reference or recommended text for graduate courses in cloud computing, service computing, and more

Principles of Marketology, Volume 2 focuses on the practical aspect and demonstrates the applications of marketology referring to market orientation, internal marketing, business, market and competitive analysis concepts and techniques. Then the modern marketology and its developments in the future are discussed. At the of this volume as the appendix, a handbook of marketology is presented in which a practical manual including simple and summarized descriptions of different needed parts and worksheets for executing marketology in an organization is depicted.

Business process management is concerned with the identification/documentation, (optimizing) design, implementation, control and improvement of operational processes in all sorts in businesses. The optimization process focuses not so much on technical issues, but rather on organizational aspects such as strategic orientation, organizational culture and providing a sense of involvement and leadership for those involved in the process. Business process management is thus one of the core competences involved in the field of strategic company management. The individual volumes in the'Executive Education'series are designed in the form of tutorial notes and are intended to be used for independent learning of the modular subject-matter and for rapid revision of the relevant lectures.

In den vorliegenden Forschungsergebnissen wird das Geschäftsmodell als Rahmenwerk zur Identifikation erfolgskritischer Komponenten genutzt, aus denen sich eine zu implementierende Steuerungslogik ableiten lässt. Hierbei werden geschäftsmodellrelevante Analyseverfahren und Kennzahlen zur Leistungsmessung verwendet, die innerhalb eines Management Dashboards prototypisch dargestellt werden. Auf Basis der dabei eingesetzten Business-Intelligence-Technologien lassen sich die erfolgskritischen Informationen detailliert analysieren, sodass eine effektive Unternehmenssteuerung ermöglicht wird.

This volume consists of papers presented at the 2014 International Symposium on Systems and Computer Technology (ISSCT 2014, Shanghai, China, 15-17 November 2014). The demand for systems and informatics have been constantly increasing, as more and more computer applications have been built. Great efforts have been made to improve the state of the a

In seiner umfangreichen Diskussion der Bedeutung von Opportunismus für das strategische Stakeholdermanagement geht Sebastian Pitschner-Finn detailliert darauf ein, wie opportunistisches Verhalten sämtlicher Stakeholder den Unternehmenserfolg gefährdet und auf welche Weise das Ausmaß dieser Gefährdung messbar und somit auch vergleichbar gemacht werden kann. Die große Breite der Diskussion lässt viel diskutierte alternative Verhaltensmuster wie Fairness und Reziprozität nicht außer Acht und ermöglicht so eine besonders kritische Auseinandersetzung mit der typischen Annahme, Opportunismus sei eine allgegenwärtige Bedingung der menschlichen Natur. Im Endergebnis der Analyse stehen allgemeingültige Handlungsempfehlungen, deren Umsetzung anhand der Verbraucher und Shareholder verdeutlicht wird. So zeigt der Autor insbesondere auf, dass die derzeitigen Opportunismusrisiken der privaten Aktionäre womöglich deutlich geringer ausfallen als oft angenommen, woraus sich wiederum passende Empfehlungen für die Maximierung des nachhaltigen Unternehmenserfolgs ergeben.

SQL is full of difficulties and traps for the unwary. You can avoid them if you understand relational theory, but only if you know how to put that theory into practice. In this book, Chris Date explains relational theory in depth, and demonstrates through numerous examples and exercises how you can apply it to your use of SQL.This third edition has been revised, extended, and improved throughout. Topics whose treatment has been expanded include data types and domains, table comparisons, image relations, aggregate operators and summarization, view updating, and subqueries. A special feature of this edition is a new appendix on NoSQL and relational theory.Could you write an SQL query to find employees who have worked at least once in every programming department in the company? And be sure it's correct?Why is proper column naming so important?Nulls in the database cause wrong answers. Why? What you can do about it?How can image relations help you formulate complex SQL queries?SQL supports'quantified comparisons,'but they're better avoided. Why? And how?Database theory and practice have evolved considerably since Codd first defined the relational model, back in 1969. This book draws on decades of experience to present the most up to date treatment of the material available anywhere. Anyone with a modest to advanced background in SQL can benefit from the insights it contains. The book is product independent.

Troubleshooting Oracle Performance, 2nd Edition is your systematic guide to diagnosing and resolving performance problems in database-backed applications involving Oracle's database engine. Christian Antognini brings a decade and a half experience to his topic. His first edition is one of the most well-respected books in its field. This second edition has been rigorously updated to cover the latest developments in Oracle Database 11g Release 2 through Oracle Database 12c. What do you do when your database application isn't running fast enough? You troubleshoot, of course. Finding the slow part of an application is often the easy part of the battle. It's finding a solution that's difficult. Troubleshooting Oracle Performance, 2nd Edition helps by providing a systematic approach to addressing the underlying causes of poor database application performance. The author freely shares his experience while explaining the underlying foundations of how SQL statements are executed by the Oracle database engine. You'll be able to draw a solid foundation of theory and shared experience as you face head-on the performance challenges in your daily work. Written for developers by an application developer who has learned by doing Gives a systematic approach to solving database application performance problems Helps you plan for performance as you would for any other application requirement

Betriebliches Informations- und Wissensmanagement steht zunehmend vor der Herausforderung verteilte Datenbestände zusammenzuführen und sinnvoll zu vernetzen. Hierbei gewinnen vor allem Semantic Web Technologien und darauf basierende Dienste an Bedeutung. Sie unterstützen die Herstellung vernetzter Wissensbasen und vereinfachen den Zugriff auf und die Veröffentlichung von verteilt vorliegenden Datensätzen sowohl innerhalb als auch außerhalb der Unternehmensgrenzen.Unter dem Begriff „Linked Enterprise Data“ demonstriert der vorliegende Band, wie Semantic Web Technologien in einer Organisation sinnvoll zum Einsatz gebracht werden können, um Mehrwert aus bestehenden Informationsbeständen zu generieren und die Fülle an qualitativ hochwertigen Datenquellen im World Wide Web für Produkt- und Service-Innovationen zu nutzen.

Die Methoden zur Datenmodellierung, die im Umfeld herkömmlicher transaktionaler Systeme eingesetzt werden, eignen sich nur bedingt für den Aufbau von Data Warehouse- und On-Line Analytical Processing- (OLAP) Systemen. Joachim Schelp setzt sich mit verschiedenen aktuellen Modellierungsmethoden und Vorgehensmodellen zum Aufbau analyseorientierter Informationssysteme auseinander. Der Autor untersucht sowohl die Eignung dieser Modelle zur Modellierung mehrdimensionaler Datenstrukturen als auch ihre qualitätsrelevanten Eigenschaften.

Zunehmende Datenvolumina in Unternehmen und Unternehmensbereichen erfordern die Entwicklung von entscheidungsunterstützenden Informationssystemen, die unter den Begriffen Data Warehouse oder Analytische Informationssysteme diskutiert werden. Lorenz Determann zeigt die Grundlagen des Data-Warehouse-Konzeptes auf, vergleicht es mit dem On-Line Analytical Processing (OLAP), stellt die bisher veröffentlichten Verfahren der multidimensionalen Datenmodellierung dar und systematisiert und bewertet sie. Auf dieser Basis entwickelt er die KOSMO-Methodik (Konzept zur semantischen Modellierung multidimensionaler Datentstrukturen) und zeigt eine Notation auf, mit deren Hilfe die Ergebnisse des Modellierungsprozesses visualisiert werden können.

Für Data Warehouse-Lösungen sind Daten aus den Informationssystemen im Unternehmen erforderlich, die der Abwicklung des Tagesgeschäfts dienen. Diese Daten müssen aufbereitet werden, damit sie entscheidungsunterstützend wirken und so den Erfolg des Data Warehouse-Projekts gewährleisten können. Jochen Müller vergleicht charakteristische Merkmale operativer und analyseorientierter Informationssysteme und untersucht die besondere Bedeutung der Schnittstellen zu den datenliefernden Vorsystemen. Anhand eines Konzepts für eine solche Schnittstellenkomponente beschreibt der Autor unterschiedliche Verfahren zur Extraktion der relevanten Daten und deren Transformation zu einem Datenbestand in einer zur Managementunterstützung angemessenen Qualität. Abschließend entwickelt der Autor ein Vorgehenskonzept, mit dessen Hilfe der Prozess der Gestaltung von Data Warehouse-Lösungen strukturiert werden kann.

Ein Data Warehouse ist in der betrieblichen Praxis häufigen Änderungen unterworfen. Einerseits kann sich die Dimensionsstruktur im Zeitablauf ändern, andererseits erweist sich der Informationsbedarf eines Entscheidungsträgers häufig als unstetig und dynamisch. Bei einer nachträglichen Beurteilung von Entscheidungssituationen ist jedoch die zum Entscheidungszeitpunkt vorherrschende Informationslage von elementarer Bedeutung. Steffen Stock erweitert das Data-Warehouse-Konzept um das Konzept der zeitbezogenen Daten, damit die zu jedem Zeitpunkt verfügbaren Daten und Klassifikationshierarchien dauerhaft gespeichert werden können. Hierzu führt der Autor eine Gültigkeitszeitmatrix ein, die eine Vergleichbarkeit der Fakten auch nach Änderungen der Klassifikationshierarchien ermöglicht. Durch diese Erweiterungen können im Zeitablauf auftretende betriebswirtschaftlich bedingte Strukturänderungen modelliert werden.

Temporal databases have been an active research topic for at least fifteen years. During this time, several dozen temporal query languages have been proposed. Many within the temporal database research community perceived that the time had come to consolidate approaches to temporal data models and calculus­ based query languages, to achieve a consensus query language and associated data model upon which future research can be based. While there were many query language proposals, with a diversity of language and modeling constructs, common themes kept resurfacing. However, the community was quite frag­ mented, with each research project being based on a particular and different set of assumptions and approaches. Often these assumptions were not germane to the research per se, but were made simply because the research required a data model or query language with certain characteristics, with the partic­ ular one chosen rather arbitrarily. It would be better in such circumstances for research projects to choose the same language. Unfortunately, no existing language had attracted a following large enough to become the one of choice. In April, 1992 Richard Snodgrass circulated a white paper that proposed that a temporal extension to SQL be produced by the research community. Shortly thereafter, the temporal database community organized the'ARPA/NSF In­ ternational Workshop on an Infrastructure for Temporal Databases,'which was held in Arlington, TX, in June, 1993.

SQL is full of difficulties and traps for the unwary. You can avoid them if you understand relational theory, but only if you know how to put the theory into practice. In this insightful book, author C.J. Date explains relational theory in depth, and demonstrates through numerous examples and exercises how you can apply it directly to your use of SQL.This second edition includes new material on recursive queries, “missing information” without nulls, new update operators, and topics such as aggregate operators, grouping and ungrouping, and view updating. If you have a modest-to-advanced background in SQL, you'll learn how to deal with a host of common SQL dilemmas.Why is proper column naming so important?Nulls in your database are causing you to get wrong answers. Why? What can you do about it?Is it possible to write an SQL query to find employees who have never been in the same department for more than six months at a time?SQL supports “quantified comparisons,” but they're better avoided. Why? How do you avoid them?Constraints are crucially important, but most SQL products don't support them properly. What can you do to resolve this situation?Database theory and practice have evolved since the relational model was developed more than 40 years ago. SQL and Relational Theory draws on decades of research to present the most up-to-date treatment of SQL available.C.J. Date has a stature that is unique within the database industry. A prolific writer well known for the bestselling textbook An Introduction to Database Systems (Addison-Wesley), he has an exceptionally clear style when writing about complex principles and theory.

The 7 revised full papers, 11 revised medium-length papers, 6 revised short, and 7 demo papers presented together with 10 poster/abstract papers describing late-breaking work were carefully reviewed and selected from numerous submissions. Provenance has been recognized to be important in a wide range of areas including databases, workflows, knowledge representation and reasoning, and digital libraries. Thus, many disciplines have proposed a wide range of provenance models, techniques, and infrastructure for encoding and using provenance. The papers investigate many facets of data provenance, process documentation, data derivation, and data annotation.

Understanding SQL's underlying theory is the best way to guarantee that your SQL code is correct and your database schema is robust and maintainable. On the other hand, if you're not well versed in the theory, you can fall into several traps. In SQL and Relational Theory, author C.J. Date demonstrates how you can apply relational theory directly to your use of SQL. With numerous examples and clear explanations of the reasoning behind them, you'll learn how to deal with common SQL dilemmas, such as: Should database access granted be through views instead of base tables? Nulls in your database are causing you to get wrong answers. Why? What can you do about it? Could you write an SQL query to find employees who have never been in the same department for more than six months at a time? SQL supports'quantified comparisons,'but they're better avoided. Why? How do you avoid them? Constraints are crucially important, but most SQL products don't support them properly. What can you do to resolve this situation? Database theory and practice have evolved since Edgar Codd originally defined the relational model back in 1969. Independent of any SQL products, SQL and Relational Theory draws on decades of research to present the most up-to-date treatment of the material available anywhere. Anyone with a modest to advanced background in SQL will benefit from the many insights in this book.

This collection contains 316 papers presented at the 2009 Structures Congress, held in Austin, Texas, April 30-May 2, 2009.

Description based on print version record.

Seit über 10 Jahren beschäftigt sich die Wirtschaftsinformatik in Forschung und Praxis mit dem Aufbau von entscheidungsrelevanten Datenbeständen unter dem Begriff Data Warehouse oder Data Warehousing, wenn man den Prozess der Datensammlung, Datenspeicherung und Datennutzung in den Vordergrund stellt. Die Grundidee bestand anfangs darin, das Berichtswesen und die betriebswirtschaftliche Analyse durch die Bereitstellung von konsistenten Unternehmensdaten zu unterstützen. Im Lauf der Zeit kamen zusätzliche Anforderungen hinzu, zu welchen auch Budgetierung und Planung gehören. Heute hat fast jedes Unternehmen ein Data Warehouse zur Unterstützung vielfältiger Entscheidungsprozesse. Insbesondere die IT-gestützte strategische Unternehmensplanung und Unternehmenskontrolle wurden im Rahmen der Einführung von analytischen Informationssystemen stark diskutiert. Dashboards und Cockpits entstanden, welche zur Realisierung von Balanced Scorecards nach Kaplan/Norton zum Einsatz kamen. Ihr Fokus liegt auf der Strategieimplementierung und der nachlaufenden Kontrolle. Bei Sichtung der einschlägigen Literatur wie auch der verfügbaren Softwarewerkzeuge ist erkennbar, dass für die vorgelagerte Phase der Strategiefindung und unternehmerischen Zielsetzung bisher kaum integrierte Ansätze zu finden sind. Um dem Anspruch der „Business Intelligence“ an ein strategisches Informationssystem näher zu kommen, reicht es nicht aus, Teilaspekte der strategischen Planung aufzugreifen oder lediglich eine Balanced Scorecard zu implementieren. Offensichtlich besteht hier eine Forschungslücke, die nicht in mangelnder betriebswirtschaftlicher Literatur oder fehlender Managementmethodiken begründet liegt, sondern in der unzureichenden Anforderungsanalyse aus Sicht derWirtschaftsinformatik. Dies mag darin begründet sein, dass vorzugsweise quantitative Planungsverfahren und Rechenvorschriften den Weg in die IT-gestützten Anwendungssysteme finden, weniger die semistrukturierten Abläufe und Dokumente der strategischen Planung.

What do you do when your database application isn't running fast enough? You troubleshoot, of course. Finding the slow part of an application is often the easy part of the battle. It's finding a solution that's difficult. Troubleshooting Oracle Performance helps by providing a systematic approach to addressing the underlying causes of poor database application performance. Written for developers by an application developer who has learned by doing Gives a systematic approach to solving database application performance problems Helps you plan for performance as you would for any other application requirement

During the past few years, determining the “value of IT” has ranked high on the agenda of IT managers and Chief Information O?cers (CIOs). The rather broad and abstract topic has been intensively discussed in the Information Systems literature for many years. It turns into a very tangible problem in the?eld of IT cost accounting. Nowadays, c- porate information systems are distributed systems. A detailed measurement of resource demands of IT services on a distributed IT-infrastructure and respective accounting and cost allocation turns out to be very expensive and impractical in most cases. The large proportion of indirect costs and the di?culty of?nding adequate allocation rates are a signi?cant problem in practice, regularly leading to free-rider problems. This problem has largely been ignored in the academic literature so far. Dr. Brandl proposes a method to derive estimators for the resource demand of service requests in a distributed IT infr- tructure. This estimator is based on a set of load tests and respective measurements as they are often performed during the deployment phase of new information systems. Cost allocation keys can now be determined based on the number of service invocations per user or per department and the respective estimators. While these measurements provide a lean method for the determination of usage-based cost allocation keys, it is not obvious that the estimators have su?cient accuracy, in p- ticular concerning di?erent types of services and volatile workloads.

The importance of managerial support has been established for modern busine- related sciences at least as early as 1922. It was then in the?rst issue of Harvard Business Review, that Wallace B. Donham called for a proper theory of business to avoid business to continue to be “unsystematic, haphazard, and for many men a pathetic gamble.” The past century witnessed signi?cant development in terms of theory. Common examples attracting considerable attention for scienti?c enquiry are decision theory, knowledge management and transfer,or organizational learning. Each set of theories focuses aspects of managerial work. Methods and tools based upon decision theory are concerned with?nding one appropriate course of actions amongst a myriad of possibilities. Knowledge management methods and tools - sentially seek to conserve and transfer expert knowledge so that repetitive errors can more easily be prevented and repeating success more easily be achieved. - nally, methods and tools building upon the notion of organizational learning aim at signi?cantly lowering the resources involved in creating experts. I focus organizational learning for two main reasons: Firstly, learning is an “- avoidable” phenomenon. Learning does not have to be pursued as an additional activity to daily responsibilities. It is thus not the question if managers learn but what they learn and how this learning process can be directed. Secondly, a new dimension of criticism emerged from postmodern discussions of knowledge m- agement or decision making, which at least hints at the need to investigate other mechanisms for supporting management.

This first-of-its-kind survey covers both the basics of information technology and the managerial and political issues surrounding the use of these technologies. Unlike other works on information systems, this book is written specifically for the public sector and addresses unique public sector issues and concerns. The technical basics are explained in clear English with as little technical jargon as possible so that readers can move on to informed analysis of the public policy issues surrounding government's use of MIS. This practical tool includes end of chapter summaries with bridges to upcoming chapters, numerous boxed exhibits, thorough end-of-chapter notes and a bibliography for further reading.

The series of International Conferences on Extending Database Technology (EDBT) is an established and prestigious forum for the exchange of the latest research results in data management. It provides unique opportunities for database researchers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences. This volume contains the proceedings of the 10th EDBT Conference, held in Munich, Germany, March 27-29, 2006. The conference included 3 keynote talks, 56 full-size and 4 half-size research papers in 20 sessions, 8 industrial presentations in 3 sessions, 1 panel session, 5 tutorials in 7 sessions, and 20 demonstrations in 4 sessions. All of the research papers as well as papers and abstracts from most of the other sessions are included here. Distinguished members of the database and information-retrieval communities delivered the three keynotes, which were all in the spirit of the banner theme chosen for EDBT 2006: “From Database Systems to Universal Data Management. ” Martin Kersten, a pioneer in the area of database support for ambient application environments and the investigator of several kernel database architectures, discussed various hard issues that arise in organic database systems, i. e., systems that can be embedded in several hardware applications and have autonomic behavior. Alan Smeaton, a leader in content-based retrieval of information in a wide variety of media, introduced us to the world of digital video libraries and challenged us with several open problems associated with their effective management.

The latest edition of a popular text and reference on database research, with substantial new material and revision; covers classical literature and recent hot topics.Lessons from database research have been applied in academic fields ranging from bioinformatics to next-generation Internet architecture and in industrial uses including Web-based e-commerce and search engines. The core ideas in the field have become increasingly influential. This text provides both students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area—the basic material for any DBMS professional. This fourth edition has been substantially updated and revised, with 21 of the 48 papers new to the edition, four of them published for the first time. Many of the sections have been newly organized, and each section includes a new or substantially revised introduction that discusses the context, motivation, and controversies in a particular area, placing it in the broader perspective of database research. Two introductory articles, never before published, provide an organized, current introduction to basic knowledge of the field; one discusses the history of data models and query languages and the other offers an architectural overview of a database system. The remaining articles range from the classical literature on database research to treatments of current hot topics, including a paper on search engine architecture and a paper on application servers, both written expressly for this edition. The result is a collection of papers that are seminal and also accessible to a reader who has a basic familiarity with database systems.

Proceedings of the 30th Annual International Conference on Very Large Data Bases held in Toronto, Canada on August 31 - September 3 2004. Organized by the VLDB Endowment, VLDB is the premier international conference on database technology.

Proceedings of the 29th Annual International Conference on Very Large Data Bases held in Berlin, Germany on September 9-12, 2003. Organized by the VLDB Endowment, VLDB is the premier international conference on database technology.

Reviews the history of computer science, discusses concepts, and profiles contributors in the field. Also explores the impact of computers on society, with examples in literature and film to illustrate and support trends. Organized in four separate topical volumes, with articles in each volume arranged A-Z. Includes illustrations, sidebars, bibliographies, filmographies, timelines, charts, and a glossary. For general audiences. 4 volumes.

Proceedings of the 28th Annual International Conference on Very Large Data Bases held in Hong Kong, China on August 20-23, 2002. Organized by the VLDB Endowment, VLDB is the premier international conference on database technology.

Real-time systems are now used in a wide variety of applications. Conventionally, they were configured at design to perform a given set of tasks and could not readily adapt to dynamic situations. The concept of imprecise and approximate computation has emerged as a promising approach to providing scheduling flexibility and enhanced dependability in dynamic real-time systems. The concept can be utilized in a wide variety of applications, including signal processing, machine vision, databases, networking, etc. For those who wish to build dynamic real-time systems which must deal safely with resource unavailability while continuing to operate, leading to situations where computations may not be carried through to completion, the techniques of imprecise and approximate computation facilitate the generation of partial results that may enable the system to operate safely and avert catastrophe. Audience: Of special interest to researchers. May be used as a supplementary text in courses on real-time systems.