A culmination of the authors' years of extensive research on the topic, this book provides a complete, self-contained introduction to advances in relational data clustering. It presents a novel theoretical framework as well as the most state-of-the-art models for relational data clustering. The authors also describe a family of new algorithms for various relational clustering problems arising in a wide range of important applications. Concepts and theory are explained through detailed application examples and the book includes a comprehensive reference list of related literature.

In Practical Financial Optimization: A Library of GAMS Models, the authors provide a diverse set of models for portfolio optimization, based on the General Algebraic Modelling System. 'GAMS' consists of a language which allows a high-level, algebraic representation of mathematical models and a set of solvers – numerical algorithms – to solve them. The system was developed in response to the need for powerful and flexible front-end tools to manage large, real-life models. The work begins with an overview of the structure of the GAMS language, and discusses issues relating to the management of data in GAMS models. The authors provide models for mean-variance portfolio optimization which address the question of trading off the portfolio expected return against its risk. Fixed income portfolio optimization models perform standard calculations and allow the user to bootstrap a yield curve from bond prices. Dedication models allow for standard portfolio dedication with borrowing and re-investment decisions, and are extended to deal with maximisation of horizon return and to incorporate various practical considerations on the portfolio tradeability. Immunization models provide for the factor immunization of portfolios of treasury and corporate bonds. The scenario-based portfolio optimization problem is addressed with mean absolute deviation models, tracking models, regret models, conditional VaR models, expected utility maximization models and put/call efficient frontier models. The authors employ stochastic programming for dynamic portfolio optimization, developing stochastic dedication models as stochastic extensions of the fixed income models discussed in chapter 4. Two-stage and multi-stage stochastic programs extend the scenario models analysed in Chapter 5 to allow dynamic rebalancing of portfolios as time evolves and new information becomes known. Models for structuring index funds and hedging interest rate risk on international portfolios are also provided. The final chapter provides a set of 'case studies': models for large-scale applications of portfolio optimization, which can be used as the basis for the development of business support systems to suit any special requirements, including models for the management of participating insurance policies and personal asset allocation. The title will be a valuable guide for quantitative developers and analysts, portfolio and asset managers, investment strategists and advanced students of finance.

Essential Skills--Made Easy! Learn how to create data models that allow complex data to be analyzed, manipulated, extracted, and reported upon accurately. Data Modeling: A Beginner's Guide teaches you techniques for gathering business requirements and using them to produce conceptual, logical, and physical database designs. You'll get details on Unified Modeling Language (UML), normalization, incorporating business rules, handling temporal data, and analytical database design. The methods presented in this fast-paced tutorial are applicable to any database management system, regardless of vendor. Designed for Easy Learning Key Skills & Concepts--Chapter-opening lists of specific skills covered in the chapter Ask the expert--Q&A sections filled with bonus information and helpful tips Try This--Hands-on exercises that show you how to apply your skills Notes--Extra information related to the topic being covered Self Tests--Chapter-ending quizzes to test your knowledge Andy Oppel has taught database technology for the University of California Extension for more than 25 years. He is the author of Databases Demystified, SQL Demystified, and Databases: A Beginner's Guide, and the co-author of SQL: A Beginner's Guide, Third Edition, and SQL: The Complete Reference, Third Edition.

This third volume of the best-selling "Data Model Resource Book" series revolutionizes the data modeling discipline by answering the question "How can you save significant time while improving the quality of any type of data modeling effort?" In contrast to the first two volumes, this new volume focuses on the fundamental, underlying patterns that affect over 50 percent of most data modeling efforts. These patterns can be used to considerably reduce modeling time and cost, to jump-start data modeling efforts, as standards and guidelines to increase data model consistency and quality, and as an objective source against which an enterprise can evaluate data models. Praise for The Data Model Resource Book, Volume 3 "Len and Paul look beneath the superficial issues of data modeling and have produced a work that is a must for every serious designer and manager of an IT project." " The Data Model Resource Book, Volume 3: Universal Patterns for Data Modeling is a great source for reusable patterns you can use to save a tremendous amount of time, effort, and cost on any data modeling effort. Len Silverston and Paul Agnewhave provided an indispensable reference of very high-quality patterns for the most foundational types of datamodel structures. This book represents a revolutionary leap in moving the data modeling profession forward." — Ron Powell, Cofounder and Editorial Director of the Business Intelligence Network "After we model a Customer, Product, or Order, there is still more about each of these that remains to be captured, such as roles they play, classifications in which they belong, or states in which they change. The Data Model Resource Book, Volume 3: Universal Patterns for Data Modeling clearly illustrates these common structures. Len Silverston and Paul Agnew have created a valuable addition to our field, allowing us to improve the consistency and quality of our models by leveraging the many common structures within this text." — Steve Hoberman, Best-Selling Author of Data Modeling Made Simple "The large national health insurance company I work at has actively used these data patterns and the (Universal Data Models) UDM, ahead of this book, through Len Silverston’s UDM Jump Start engagement. The patterns have found their way into the core of our Enterprise Information Model, our data warehouse designs, and progressively into key business function databases. We are getting to reuse the patterns across projects and are reaping benefits in understanding, flexibility, and time-to-market. Thanks so much." — David Chasteen, Enterprise Information Architect "Reusing proven data modeling design patterns means exactly that. Data models become stable, but remain very flexible to accommodate changes. We have had the fortune of having Len and Paul share the patterns that are described in this book via our engagements with Universal Data Models, LLC. These data modeling design patterns have helped us to focus on the essential business issues because we have leveraged these reusable building blocks for many of the standard design problems. These design patterns have also helped us to evaluate the quality of data models for their intended purpose. Many times there are a lot of enhancements required. Too often the very specialized business-oriented data model is also implemented physically. This may have significant drawbacks to flexibility. I’m looking forward to increasing the data modeling design pattern competence within Nokia with the help of this book." — Teemu Mattelmaki, Chief Information Architect, Nokia "Once again, Len Silverston, this time together with Paul Agnew, has made a valuable contribution to the body of knowledge about datamodels, and the act of building sound data models. As a professional data modeler, and teacher of data modeling for almost three decades, I have always been aware that I had developed some familiar mental "patterns" which I acquired very early in my data modeling experience. When teaching data modeling, we use relatively simple workshops, but they are carefully designed so the students will see and acquire a lot of these basic "patterns" — templates that they will recognize and can use to interpret different subject matter into data model form quickly and easily. I’ve always used these patterns in the course of facilitating data modeling sessions; I was able to recognize "Ah, this is just like . . .," and quickly apply a pattern that I’d seen before. But, in all this time, I’ve never sat down and clearly categorized and documented what each of these “patterns’’ actually was in such a way that they could be easily and clearly communicated to others; Len and Paul have done exactly that. As in the other Data Model Resource Books, the thinking and writing is extraordinarily clear and understandable. I personally would have been very proud to have authored this book, and I sincerely applaud Len and Paul for another great contribution to the art and science of data modeling. It will be of great value to any data modeler." — William G. Smith, President, William G. Smith & Associates, www.williamgsmith.com "Len Silverston and Paul Agnew’s book, Universal Patterns for Data Modeling, is essential reading for anyone undertaking commercial datamodeling. With this latest volume that compiles and insightfully describes fundamental, universal data patterns, The Data Model Resource Book series represents the most important contribution to the data modeling discipline in the last decade." — Dr. Graeme Simsion, Author of Data Modeling Essentials and Data Modeling Theory and Practice "Volume 3 of this trilogy is a most welcome addition to Len Silverston’s two previous books in this area. Guidance has existed for some time for those who desire to use pattern-based analysis to jump-start their data modeling efforts. Guidance exists for those who want to use generalized and industry-specific data constructs to leverage their efforts. What has been missing is guidance to those of us needing guidance to complete the roughly one-third of data models that are not generalized or industry-specific. This is where the magic of individual organizational strategies must manifest itself, and Len and Paul have done so clearly and articulately in a manner that complements the first two volumes of The Data Model Resource Book. By adding this book to Volumes 1 and 2 you will be gaining access to some of the most integrated data modeling guidance available on the planet." — Dr. Peter Aiken, Author of XML in Data Management and data management industry leader VCU/Data Blueprint

As business modeling becomes mainstream, every year more and more companies and government agencies are creating models of their businesses. But creating good business models is not a simple endeavor. Business modeling requires new skills. Written by two business modeling experts, this book shows you how to make your business modeling efforts successful. It provides in-depth coverage of each of the four distinct business modeling disciplines, helping you master them all and understand how to effectively combine them. It also details best practices for working with subject matter experts. And it shows how to develop models, and then analyze, simulate, and deploy them. This is essential, authoritative information that will put you miles ahead of everyone who continues to approach business modeling haphazardly. Provides in-depth coverage of the four business modeling disciplines: process modeling, motivation modeling, organization modeling, and rules modeling Offers guidance on how to work effectively with subject matter experts and how to run business modeling workshops Details today's best practices for building effective business models, and describes common mistakes that should be avoided Describes standards for each business modeling discipline Explains how to analyze, simulate, and deploy business models Includes examples both from the authors' work with clients and from a single running example that spans the book

Commodity Modeling and Pricing provides extensions and applications of state-of-the-art methods for analyzing resource commodity behavior. Drawing from the seminal work of Professor Walter Labys on the development of econometric methods for forecasting commodity prices, this collection of essays features expert contributors ranging from practitioners in private industry, public sector, and nongovernmental organizations to scholars in higher education-all of whom were Labys's former students or collaborators. Filled with in-depth insights and expert advice, Commodity Modeling and Pricing contains the information you need to excel in this demanding environment.

“ explains the concepts and practice of data modeling with a clarity that makes the technology accessible to anyone building databases and data-driven applications. A Developer’s Guide to Data Modeling for SQL Server “Eric Johnson and Joshua Jones combine a deep understanding of the science of data modeling with the art that comes with years of experience. If you’re new to data modeling, or find the need to brush up on its concepts, this book is for you.” — Peter Varhol, Executive Editor, Redmond Magazine Model SQL Server Databases That Work Better, Do More, and Evolve More Smoothly Effective data modeling is essential to ensuring that your databases will perform well, scale well, and evolve to meet changing requirements. However, if you’re modeling databases to run on Microsoft SQL Server 2008 or 2005, theoretical or platform-agnostic data modeling knowledge isn’t enough: models that don’t reflect SQL Server’s unique real-world strengths and weaknesses often lead to disastrous performance. is a practical, SQL Server-specific guide to data modeling for every developer, architect, and administrator. This book offers you invaluable start-to-finish guidance for designing new databases, redesigning existing SQL Server data models, and migrating databases from other platforms. A Developer’s Guide to Data Modeling for SQL Server You’ll begin with a concise, practical overview of the core data modeling techniques. Next, you’ll walk through requirements gathering and discover how to convert requirements into effective SQL Server logical models. Finally, you’ll systematically transform those logical models into physical models that make the most of SQL Server’s extended functionality. All of this book’s many examples are available for download from a companion Web site. This book enables you to Understand your data model’s physical elements, from storage to referential integrity Provide programmability via stored procedures, user-defined functions, triggers, and .NET CLR integration Normalize data models, one step at a time Gather and interpret requirements more effectively Learn an effective methodology for creating logical models Overcome modeling problems related to entities, attribute, data types, storage overhead, performance, and relationships Create physical models—from establishing naming guidelines through implementing business rules and constraints Use SQL Server’s unique indexing capabilities, and overcome their limitations Create abstraction layers that enhance security, extensibility, and flexibility

John Morecroft's book is an ideal text for students interested in system modelling and its application to a range of real world problems. The book covers all that is necessary to develop expertise in system dynamics modelling and through the range of applications makes a persuasive case for the power and scope of the approach. As such it will appeal to practitioners as well as students. Robert Dyson, Professor of Operational Research, Associate Dean, Warwick Business School. Much more than an introduction, John Morecroft's Strategic Modelling and Business Dynamics uses interactive "management flight simulators" to create an engaging and effective learning environment in which readers, whatever their background, can develop their intuition about complex dynamic systems. The numerous examples provide a rich test-bed for the development of systems thinking and modelling skills John Sterman, Jay W. Forrester Professor of Management, MIT Sloan School of Management This book, with its vivid examples and simulators, will help to bring modelling, system dynamics and simulation into the mainstream of management education where they now belong. John A. Quelch, Professor of Marketing, Harvard Business School, Former Dean of London Business School This text fills the gap between texts focusing on the purely descriptive systems approach and the more technical system dynamics ones. Ann van Ackere, Professor of Decision Sciences, HEC Lausanne, Universit? de Lausanne Strategic modelling based on system dynamics is a powerful tool for understanding how firms adapt to a changing environment. The author demonstrates the appeal and power of business modelling to make sense of strategic initiatives and to anticipate their impacts through simulation. The book offers various simulators that allow readers to conduct their own policy experiments. Dr. Erich Zahn, Professor of Strategic Management, Betriebswirtschaftliches Institut, University of Stuttgart A website to accompany the book can be found at www.wiley.com/college/morecroft housing supplementary material for both students and lecturers.

The state-of-the-art publication in model-based process control—by leading experts in the field. In Techniques of Model-Based Control, two leading experts bring together powerful advances in model-based control for chemical-process engineering. Coleman Brosilow and Babu Joseph focus on practical approaches designed to solve real-world problems, and they offer extensive examples and exercises. Coverage includes: The nature of the process-control problem and how model-based solutions help to solve it Continuous time modeling: time domain, Laplace domain, and FOPDT models Feedforward, cascade, override, and single-variable inferential control approaches One and two degree of freedom Internal Model Control Model State Feedback and PI/PID Implementations of IMC Tuning and synthesis of 1DF and 2DF IMC for process uncertainty Estimation and inferential control using multiple secondary measurements Basic and advanced techniques of model identification and model-predictive control The appendices review the basics of Laplace transforms, feedback control, frequency response analysis, probability, random variables, and linear least-square regression. From start to finish, Techniques of Model-Based Control offers the real-world insight that professionals need to identify and implement the best control strategies for virtually any process.

A rigorous and practical framework for modeling business systems Pares object modeling down to its core concepts, making it easier than ever. Twelve object collaboration patterns that address virtually any business scenario Powerful techniques–not fancy notation! Streamlined Object Modeling presents the first rigorous, practical framework for object modeling complex business domains, rules, and systems. Three world-renowned leaders in object development have pared object modeling down to the core concepts for all business domains, business rules, and business services. Starting from the first principles of "object think," the authors offer a fully integrated approach to building, validating, and critiquing object models. Coverage includes: Proven principles and techniques for successfully modeling the structure and operations of any business domain. Guidelines for finding and associating objects, assembling object models, and distributing system behavior among objects. Rigorous methods for discovering, organizing, and implementing business rules around objects. Twelve all-encompassing "collaboration patterns"–what they represent, how they relate, and how to apply them. Five kinds of business rules, three types of services, and six categories of properties completely specify object-oriented business requirements From start to finish, the book makes extensive use of examples drawn from real commercial applications. To illustrate how streamlined object modeling flows from analysis to code, it also presents a complete case study derived from a real-world application, and implemented in two leading object-oriented languages-Java, and the Squeak implementation of Smalltalk.

A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful 1st Edition, while adding a companion volume to take care of more specific requirements of different businesses. This updated volume provides a common set of data models for specific core functions shared by most businesses like human resources management, accounting, and project management. These models are standardized and are easily replicated by developers looking for ways to make corporate database development more efficient and cost effective. This guide is the perfect complement to The Data Model Resource CD-ROM, which is sold separately and provides the powerful design templates discussed in the book in a ready-to-use electronic format. A free demonstration CD-ROM is available with each copy of the print book to allow you to try before you buy the full CD-ROM.

A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful First Edition, while adding a companion volume to take care of more specific requirements of different businesses. Each volume is accompanied by a CD-ROM, which is sold separately. Each CD-ROM provides powerful design templates discussed in the books in a ready-to-use electronic format, allowing companies and individuals to develop the databases they need at a fraction of the cost and a third of the time it would take to build them from scratch. With each business function boasting its own directory, this CD-ROM provides a variety of data models for specific implementations in such areas as financial services, insurance, retail, healthcare, universities, and telecom.

"This book isn't just another introduction to use cases. The authors have used their wealth of experience to produce an excellent and insightful collection of detailed examples, explanations, and advice on how to work with use cases." –Maria Ericsson The toughest challenge in building a software system that meets the needs of your audience lies in clearly understanding the problems that the system must solve. Advanced Use Case Modeling presents a framework for discovering, identifying, and modeling the problem that the software system will ultimately solve. Software developers often employ use cases to specify what should be performed by the system they're constructing. Although use case-driven analysis, design, and testing of software systems has become increasingly popular, little has been written on the role of use cases in the complete software cycle. This book fills that need by describing how to create use case models for complex software development projects, using practical examples to explain conceptual information. The authors extend the work of software visionary Ivar Jacobson, using the Unified Modeling Language (UML) as the notation to describe the book's models. Aimed primarily at software professionals, Advanced Use Case Modeling also includes information that relates use case technique to business processes. This book presents a process for creating and maintaining use case models in a framework that can be fully customized for your organization. The authors, pioneers in the application of use cases in software development, bring their extensive experience to cover topics such as: A process model for applying a use case model How to keep your use case modeling effort on track Tips and pitfalls in use case modeling How to organize your use case model for large-system development Similarities between Advanced Use Case Modeling and the Rational Unified Process framework Effect of use cases on user interface design Guidelines for quality use case modeling

Data modeling is one of the most critical phases in the database application development process, but also the phase most likely to fail. A master data modeler must come into any organization, understand its data requirements, and skillfully model the data for applications that most effectively serve organizational needs. is a complete guide to becoming a successful data modeler. Featuring a requirements-driven approach, this book clearly explains fundamental concepts, introduces a user-oriented data modeling notation, and describes a rigorous, step-by-step process for collecting, modeling, and documenting the kinds of data that users need. Mastering Data Modeling Assuming no prior knowledge, sets forth several fundamental problems of data modeling, such as reconciling the software developer's demand for rigor with the users' equally valid need to speak their own (sometimes vague) natural language. In addition, it describes the good habits that help you respond to these fundamental problems. With these good habits in mind, the book describes the Logical Data Structure (LDS) notation and the process of controlled evolution by which you can create low-cost, user-approved data models that resist premature obsolescence. Also included is an encyclopedic analysis of all data shapes that you will encounter. Most notably, the book describes The Flow, a loosely scripted process by which you and the users gradually but continuously improve an LDS until it faithfully represents the information needs. Essential implementation and technology issues are also covered. Mastering Data Modeling You will learn about such vital topics as: The fundamental problems of data modeling The good habits that help a data modeler be effective and economical LDS notation, which encourages these good habits How to read an LDS aloud--in declarative English sentences How to write a well-formed (syntactically correct) LDS How to get users to name the parts of an LDS with words from their own business vocabulary How to visualize data for an LDS A catalog of LDS shapes that recur throughout all data models The Flow--the template for your conversations with users How to document an LDS for users, data modelers, and technologists How to map an LDS to a relational schema How LDS differs from other notations and why "Story interludes" appear throughout the book, illustrating real-world successes of the LDS notation and controlled evolution process. Numerous exercises help you master critical skills. In addition, two detailed, annotated sample conversations with users show you the process of controlled evolution in action.

This issue discusses several evaluation models, methods, and tools used to evaluate different types of performance interventions. It compares evaluation models in the context of soft data, and discusses how performance interventions can be jeopardized.

Water Management Models: A Guide to Software is designed to make the inventory of modeling tools more accessible to water management professionals. The purpose of the book is to assist water managers, planners, engineers, and scientists in sorting through the maze of models to understand which ones might be most useful for their particular modeling needs. Information is provided to facilitate identification, selection, and acquisition of software packages for a broad spectrum of water resources planning and management applications.