Das Internet ist inzwischen ein fester Bestandteil des Alltags. Die Autoren erl utern die technologischen Grundlagen, auf denen es beruht. Ausgehend von den physikalischen Grundlagen der Daten bertragung erfahren Leser, nach welchen Prnzipien und auf Grundlage welcher Technologien lokale Netzwerke (LANs) und Weitverkehrsnetzwerke (WANs) funktionieren. Das Kompendium zur Internet-Technologie vermittelt allgemein verst ndlich das dem Internet zugrunde liegende TCP/IP-Referenzmodell sowie dessen Protokolle und zahlreichen Anwendungen.

Kundennahe und Kundenorientierung gelten als Schlusselfaktoren zum Geschaftserfolg. Dies impliziert eine konsequente Ausrichtung von unternehmensinternen und -ubergreifenden Geschaftsprozessen auf den "Koenig Kunde". Mit diesem Themenkreis setzt sich der Schwerpunkt Geschaftsprozessmanagement auseinander. Im Abschnitt Kosten- und Deckungsbeitragsmanagement muss sich das Controlling einer kritischen Betrachtung des kundenorientierten Arbeitens unterziehen. Neuere Entwicklungen wie Data Warehousing und die Nutzung des Internet als Moeglichkeit zur Annaherung an den Kunden werden u.a. im Abschnitt Informationsmanagement diskutiert. Loesungsansatze fur den Einsatz betriebswirtschaftlicher Methoden und moderner Kommunikationstechnologie in der oeffentlichen Verwaltung bietet der Abschnitt Verwaltungsmanagement.

Data science unifies statistics, data analysis and machine learning to achieve a better understanding of the masses of data which are produced today, and to improve prediction. Special kinds of data (symbolic, network, complex, compositional) are increasingly frequent in data science. These data require specific methodologies, but there is a lack of reference work in this field. Advances in Data Science fills this gap. It presents a collection of up-to-date contributions by eminent scholars following two international workshops held in Beijing and Paris. The 10 chapters are organized into four parts: Symbolic Data, Complex Data, Network Data and Clustering. They include fundamental contributions, as well as applications to several domains, including business and the social sciences.

Real-Time Enterprise (RTE) ist eine Unternehmensstruktur, die durch kontinuierliche Beschleunigung der Managementprozesse die eigene Aktions- und Reaktionsgeschwindigkeit nachhaltig verbessert und verzogerungsfrei auf externe sowie interne Anderungen reagieren und damit Zeit und Kosten einsparen kann. Voraussetzungen und Rahmenbedingungen hierfur sind durchgangig integrierte Geschaftsprozesse und Informationsflusse entlang der kompletten Wertschopfungskette. Im Idealfall sind dabei alle Arbeitsprozesse in einem Unternehmen optimal aufeinander abgestimmt, so dass Data Warehouse, Supply Chain Management, Customer Relationship Management und Enterprise Resource Planning wirkungsvoll ineinander greifen. Dabei endet die Betrachtung von Prozessen und Informationen nicht an den Unternehmensgrenzen. Statt dessen sind Kunden und beteiligte Partnerfirmen beziehungsweise deren Prozesse transparent eingebunden und tauschen Informationen uber alle relevanten Ereignisse zeitnah aus. "

Sir Walter Raleigh wollte wissen, wie Kanonenkugeln in einem Schiff am dichtesten gestapelt werden koennen. Der Astronom Johannes Kepler lieferte im Jahr 1611 die Antwort: genau so, wie Gemusehandler ihre Orangen und Tomaten aufstapeln. Noch war dies lediglich eine Vermutung - erst 1998 gelang dem amerikanischen Mathematiker Thomas Hales mit Hilfe von Computern der mathematische Beweis. Einer der besten Autoren fur popularwissenschaftliche Mathematik beschreibt auf faszinierende Art und Weise ein beruhmtes mathematisches Problem und dessen Loesung.

To date, statistics has tended to be neatly divided into two theoretical approaches or frameworks: frequentist (or classical) and Bayesian. Scientists typically choose the statistical framework to analyse their data depending on the nature and complexity of the problem, and based on their personal views and prior training on probability and uncertainty. Although textbooks and courses should reflect and anticipate this dual reality, they rarely do so. This accessible textbook explains, discusses, and applies both the frequentist and Bayesian theoretical frameworks to fit the different types of statistical models that allow an analysis of the types of data most commonly gathered by life scientists. It presents the material in an informal, approachable, and progressive manner suitable for readers with only a basic knowledge of calculus and statistics. Statistical Modeling with R is aimed at senior undergraduate and graduate students, professional researchers, and practitioners throughout the life sciences, seeking to strengthen their understanding of quantitative methods and to apply them successfully to real world scenarios, whether in the fields of ecology, evolution, environmental studies, or computational biology.

With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market. Comparing and contrasting the different types of analysis commonly conducted with big data, this accessible reference presents clear-cut explanations of the general workings of big data tools. Instead of spending time on HOW to install specific packages, it focuses on the reasons WHY readers would install a given package. The book provides authoritative guidance on a range of tools, including open source and proprietary systems. It details the strengths and weaknesses of incorporating big data analysis into decision-making and explains how to leverage the strengths while mitigating the weaknesses. Describes the benefits of distributed computing in simple terms Includes substantial vendor/tool material, especially for open source decisions Covers prominent software packages, including Hadoop and Oracle Endeca Examines GIS and machine learning applications Considers privacy and surveillance issues The book further explores basic statistical concepts that, when misapplied, can be the source of errors. Time and again, big data is treated as an oracle that discovers results nobody would have imagined. While big data can serve this valuable function, all too often these results are incorrect, yet are still reported unquestioningly. The probability of having erroneous results increases as a larger number of variables are compared unless preventative measures are taken. The approach taken by the authors is to explain these concepts so managers can ask better questions of their analysts and vendors as to the appropriateness of the methods used to arrive at a conclusion. Because the world of science and medicine has been grappling with similar issues in the publication of studies, the authors draw on their efforts and apply them to big data.

Der Mangel an qualifizierten Softwareentwicklern im deutschsprachigen Raum verscharft sich. Die effektive Zusammenarbeit in weltweit verteilten Teams ist daher ein entscheidender Wettbewerbsfaktor und Offshoring wird immer relevanter. Der Autor moechte das Thema auch kleinen und mittleren Unternehmen naher bringen und die Eintrittsbarrieren fur kostengunstige Offshore-Softwareentwicklungen reduzieren. Er zeigt, wie Unternehmen erfolgreich Offshore-Projekte umsetzen koennen: praxisnah, mit konkreten Fallstudien und Hinweisen zur Projektabwicklung. Dem Leser werden Werkzeuge vermittelt, mit denen er die Risiken in der Abwicklung von Offshore-Projekten reduzieren kann, ohne dass Kostenvorteile verloren gehen.

What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture. This practical book shows you how true data-drivenness involves processes that require genuine buy-in across your company, from analysts and management to the C-Suite and the board. Through interviews and examples from data scientists and analytics leaders in a variety of industries, author Carl Anderson explains the analytics value chain you need to adopt when building predictive business models-from data collection and analysis to the insights and leadership that drive concrete actions. You'll learn what works and what doesn't, and why creating a data-driven culture throughout your organization is essential.Start from the bottom up: learn how to collect the right data the right way Hire analysts with the right skills, and organize them into teams Examine statistical and visualization tools, and fact-based story-telling methods Collect and analyze data while respecting privacy and ethics Understand how analysts and their managers can help spur a data-driven culture Learn the importance of data leadership and C-level positions such as chief data officer and chief analytics officer

Das Buch soll Mainframe-Anwendern helfen, die Philosophie von Datenbanken zu verstehen und selbst Datenbankrecherchen zu formulieren. Hierfur stellt IBMs Query Management Facility, kurz QMF, eine sehr geschickt komponierte Sammlung von Werkzeugen zur Verfugung. Das Buch richtet sich an Endanwender und zeigt, wie man mit Hilfe von QMF fachliche Probleme loesen kann, auch ohne die Entwicklungsabteilung zu bemuhen. Die beigefugte CD-ROM enthalt die Tabellen, die allen Beispielen zugrunde liegen, als ASCII-Dateien und ermoeglicht die praktische Durchfuhrung der Fallbeispiele mit dem Computer.

This book provides a first-hand account of business analytics and its implementation, and an account of the brief theoretical framework underpinning each component of business analytics. The themes of the book include (1) learning the contours and boundaries of business analytics which are in scope; (2) understanding the organization design aspects of an analytical organization; (3) providing knowledge on the domain focus of developing business activities for financial impact in functional analysis; and (4) deriving a whole gamut of business use cases in a variety of situations to apply the techniques. The book gives a complete, insightful understanding of developing and implementing analytical solution.

In dem Buch werden Methoden vorgestellt, mit denen ubersehenes IT-Potenzial in Organisation genutzt werden kann. Dabei geht die Autorin davon aus, dass das Wissen bereits vorhanden ist und nur gehoben werden muss. Mit Checklisten und Tipps fur die Umsetzung."

Die automatische Auswertung von Signalen spielt in der modernen Informationstechnik eine grosse Rolle. Dieses Lehrbuch bietet, ausgehend von der Reprasentation des Signals im Merkmalraum, die Beschreibung wichtiger Klassifikationsverfahren. Dazu zahlen Linear- und Bayes Klassifikatoren, Supportvektormaschinen, Klassifikatoren auf der Basis von Gaussian-Mixture-Modellen und Hidden-Markov-Modellen sowie Klassenfolgenklassifikatoren.Weiterhin werden wichtige Grundlagen der Automatentheorie (Finite State Machines) sowie ausgewahlte maschinelle Lernverfahren dargestellt.Die Darstellung setzt die Verfahren zur Merkmalgewinnung voraus, die im ersten Band vermittelt wurden, so dass das Gesamtwerk eine umfassende Beschreibung der Kette darstellt, die in modernen Systemen der Informationsverarbeitung von der Signalerfassung bis hin zum Klassifikationsergebnis fuhrt.

The last decade has witnessed the rise of big data in game development as the increasing proliferation of Internet-enabled gaming devices has made it easier than ever before to collect large amounts of player-related data. At the same time, the emergence of new business models and the diversification of the player base have exposed a broader potential audience, which attaches great importance to being able to tailor game experiences to a wide range of preferences and skill levels. This, in turn, has led to a growing interest in data mining techniques, as they offer new opportunities for deriving actionable insights to inform game design, to ensure customer satisfaction, to maximize revenues, and to drive technical innovation. By now, data mining and analytics have become vital components of game development. The amount of work being done in this area nowadays makes this an ideal time to put together a book on this subject. Data Analytics Applications in Gaming and Entertainment seeks to provide a cross section of current data analytics applications in game production. It is intended as a companion for practitioners, academic researchers, and students seeking knowledge on the latest practices in game data mining. The chapters have been chosen in such a way as to cover a wide range of topics and to provide readers with a glimpse at the variety of applications of data mining in gaming. A total of 25 authors from industry and academia have contributed 12 chapters covering topics such as player profiling, approaches for analyzing player communities and their social structures, matchmaking, churn prediction and customer lifetime value estimation, communication of analytical results, and visual approaches to game analytics. This book's perspectives and concepts will spark heightened interest in game analytics and foment innovative ideas that will advance the exciting field of online gaming and entertainment.

Sprachtechnologie in der Anwendung" wurde von Praktikern fur Praktiker geschrieben. Das Buch fuhrt ein in die Technologien zur Sprachverarbeitung und informiert uber den Stand der Technik von Sprachdialogsystemen. Es unterstutzt die Entscheidungsfindung und Vorbereitung bei der Einfuhrung eines Sprachportals, hilft bei der Auswahl der richtigen Systeme und der Vermeidung von Stolpersteinen.

Durch seine klare Sprache, die zahlreichen Praxisbeispiele und das ausfuhrliche Glossar schlagt das Buch eine Brucke zwischen Entscheidern und Technologen im Unternehmen. Es wendet sich sowohl an Manager, die uber die Einfuhrung von Sprachportalen entscheiden, als auch IT-Fachleute, die diese umsetzen. Betreiber von Sprachportalen unterstutzt es bei der Bewertung bestehender Anwendungen und gibt Hinweise zu deren Optimierung."

By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments.
Readable and accessible, Big Data Analytics Strategies for the Smart Grid addresses the needs of applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. It supplies industry stakeholders with an in-depth understanding of the engineering, business, and customer domains within the power delivery market.
The book explores the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers. It not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls.
Discussing security and data privacy, it explores the role of the utility in protecting their customers right to privacy while still engaging in forward-looking business practices. The book includes discussions of:

• SAS for asset management tools
• The AutoGrid approach to commercial analytics
• Space-Time Insight s work at the California ISO (CAISO)

This book is an ideal resource for mid- to upper-level utility executives who need to understand the business value of smart grid data analytics. It explains critical concepts in a manner that will better position executives to make the right decisions about building their analytics programs.
At the same time, the book provides sufficient technical depth that it is useful for data analytics professionals who need to better understand the nuances of the engineering and business challenges unique to the utilities industry.
"

Das Buch beschreibt die Potenziale zwischenbetrieblicher Kooperationen in Logistiknetzwerken sowie den unternehmensubergreifenden Einsatz von mySAP.com-Losungen. Im Mittelpunkt stehen Anwendungen aus den Bereichen XML/EDI, Data Warehouse, Supply-Chain-Management und Elektronische Marktplatze. Anhand von funf Fallstudien aus der Automobilindustrie wird der Praxiseinsatz von mySAP.com-Losungen demonstriert. Bei den Anwendern handelt es sich um die Unternehmen Bosch GmbH, Goodyear Tire & Rubber Company, Schenker AG, Porsche AG sowie den Elektronischen Marktplatz SupplyOn.
Die vorliegende zweite Auflage wurde vollig uberarbeitet, um den aktuellen Herausforderungen an den Aufbau von Kooperationen sowohl aus Management- als auch aus Softwareperspektive Rechnung zu tragen. Dazu wurde zum einen das Autorenteam erweitert und zum anderen der Fallstudienteil der ersten Auflage ausgebaut."

Environmental science (ecology, conservation, and resource management) is an increasingly quantitative field. A well-trained ecologist now needs to evaluate evidence generated from complex quantitative methods, and to apply these methods in their own research. Yet the existing books and academic coursework are not adequately serving most of the potential audience - instead they cater to the specialists who wish to focus on either mathematical or statistical aspects, and overwhelmingly appeal to those who already have confidence in their quantitative skills. At the same time, many texts lack an explicit emphasis on the epistemology of quantitative techniques. That is, how do we gain understanding about the real world from models that are so vastly simplified? This accessible textbook introduces quantitative ecology in a manner that aims to confront these limitations and thereby appeal to a far wider audience. It presents material in an informal, approachable, and encouraging manner that welcomes readers with any degree of confidence and prior training. It covers foundational topics in both mathematical and statistical ecology before describing how to implement these concepts to choose, use, and analyse models, providing guidance and worked examples in both spreadsheet format and R. The emphasis throughout is on the skilful interpretation of models to answer questions about the natural world. Introduction to Quantitative Ecology is suitable for advanced undergraduate students and incoming graduate students, seeking to strengthen their understanding of quantitative methods and to apply them successfully to real world ecology, conservation, and resource management scenarios.

Demography is everywhere in our lives: from birth to death. Indeed, the universal currencies of survival, development, reproduction, and recruitment shape the performance of all species, from microbes to humans. The number of techniques for demographic data acquisition and analyses across the entire tree of life (microbes, fungi, plants, and animals) has drastically increased in recent decades. These developments have been partially facilitated by the advent of technologies such as GIS and drones, as well as analytical methods including Bayesian statistics and high-throughput molecular analyses. However, despite the universality of demography and the significant research potential that could emerge from unifying: (i) questions across taxa, (ii) data collection protocols, and (iii) analytical tools, demographic methods to date have remained taxonomically siloed and methodologically disintegrated. This is the first book to attempt a truly unified approach to demography and population ecology in order to address a wide range of questions in ecology, evolution, and conservation biology across the entire spectrum of life. This novel book provides the reader with the fundamentals of data collection, model construction, analyses, and interpretation across a wide repertoire of demographic techniques and protocols. It introduces the novice demographer to a broad range of demographic methods, including abundance-based models, life tables, matrix population models, integral projection models, integrated population models, individual based models, and more. Through the careful integration of data collection methods, analytical approaches, and applications, clearly guided throughout with fully reproducible R scripts, the book provides an up-to-date and authoritative overview of the most popular and effective demographic tools. Demographic Methods across the Tree of Life is aimed at graduate students and professional researchers in the fields of demography, ecology, animal behaviour, genetics, evolutionary biology, mathematical biology, and wildlife management.

Kann man mit E-Government die Verwaltung optimieren? Eine empirische Studie zur Prozessorientierung von E-Government-Initiativen auf Bundes- und Landesebene steht im Mittelpunkt des Buches. Sie zeigt, dass der Nutzen von E-Government-LAsungen entscheidend davon abhAngt, inwiefern die bestehenden VerwaltungsablAufe verbessert werden kAnnen. Obwohl diese Erkenntnis von der Mehrheit der befragten EntscheidungstrAger unterstA1/4tzt wird, ist das Thema Prozessoptimierung in vielen laufenden E-Government-Projekten noch nicht strukturiert umgesetzt. Vielfach dominiert noch die Technikeuphorie.

Neben einer Bestandsaufnahme der laufenden E-Government-Initiativen in Deutschland bietet das Buch ausfA1/4hrliche Empfehlungen, wie ein systematisches Prozessmanagement in die E-Government-Programme der Affentlichen Verwaltung integriert werden kann. Fazit: Kein E-Government-Erfolg ohne ProzessverAnderung

What is latent class analysis? If you asked that question thirty or forty years ago you would have gotten a different answer than you would today. Closer to its time of inception, latent class analysis was viewed primarily as a categorical data analysis technique, often framed as a factor analysis model where both the measured variable indicators and underlying latent variables are categorical. Today, however, it rests within much broader mixture and diagnostic modeling framework, integrating measured and latent variables that may be categorical and/or continuous, and where latent classes serve to define the subpopulations for whom many aspects of the focal measured and latent variable model may differ. For latent class analysis to take these developmental leaps required contributions that were methodological, certainly, as well as didactic. Among the leaders on both fronts was C. Mitchell "Chan" Dayton, at the University of Maryland, whose work in latent class analysis spanning several decades helped the method to expand and reach its current potential. The current volume in the Center for Integrated Latent Variable Research (CILVR) series reflects the diversity that is latent class analysis today, celebrating work related to, made possible by, and inspired by Chan's noted contributions, and signaling the even more exciting future yet to come.

Immer mehr Kreative nutzen die Moglichkeit, eigene dreidimensionale Objekte in Kunststoff, Metall oder Keramik schnell und preisgunstig herstellen zu lassen. Der 3D-Druck ist eine revolutionare Technologie, die dieVerwirklichung von Ideen ermoglicht. 3D-Drucker werden immer kleiner und leistungsstarker und damit burotauglicher. Eine umfassende Beschreibung dieser Zukunftstechnologie bietet dieses praxisnahe und anwenderorientierte Buch. Dabei hilft es mit Tipps und Hinweisen bei der Auswahl des optimalen CAD-Programms und 3D-Druckers."

Building a simple but powerful recommendation system is much easier than you think. Approachable for all levels of expertise, this report explains innovations that make machine learning practical for business production settings--and demonstrates how even a small-scale development team can design an effective large-scale recommendation system. Apache Mahout committers Ted Dunning and Ellen Friedman walk you through a design that relies on careful simplification. You'll learn how to collect the right data, analyze it with an algorithm from the Mahout library, and then easily deploy the recommender using search technology, such as Apache Solr or Elasticsearch. Powerful and effective, this efficient combination does learning offline and delivers rapid response recommendations in real time. Understand the tradeoffs between simple and complex recommenders Collect user data that tracks user actions--rather than their ratings Predict what a user wants based on behavior by others, using Mahoutfor co-occurrence analysis Use search technology to offer recommendations in real time, complete with item metadata Watch the recommender in action with a music service example Improve your recommender with dithering, multimodal recommendation, and other techniques

Statistical methods are a key tool for all scientists working with data, but learning the basics continues to challenge successive generations of students. This accessible textbook provides an up-to-date introduction to the classical techniques and modern extensions of linear model analysis-one of the most useful approaches for investigating scientific data in the life and environmental sciences. While some of the foundational analyses (e.g. t tests, regression, ANOVA) are as useful now as ever, best practice moves on and there are many new general developments that offer great potential. The book emphasizes an estimation-based approach that takes account of recent criticisms of over-use of probability values and introduces the alternative approach that uses information criteria. This new edition includes the latest advances in R and related software and has been thoroughly "road-tested" over the last decade to create a proven textbook that teaches linear and generalized linear model analysis to students of ecology, evolution, and environmental studies (including worked analyses of data sets relevant to all three disciplines). While R is used throughout, the focus remains firmly on statistical analysis. The New Statistics with R is suitable for senior undergraduate and graduate students, professional researchers, and practitioners in the fields of ecology, evolution and environmental studies.