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      • Fiction
        July 2020

        Las batallas silenciadas

        by Nives Muñoz

        MUCHAS VIDAS SE PERDIERON. PERO TAMBI & Eacute; N MUCHAS ALMAS PERMANECERON EN SUSPENSI & Oacute; N ... Verdun, 1916. Cuando comienza la Guerra Mundial, Ir & egrave; ne Curie toma una decisi & oacute; n: estar & aacute; lo m & aacute; s cerca posible del frente. Convencido de que puede ayudar a salvar muchas vidas, pasar & aacute; su & uacute; ltimo aliento ense & ntilde; ando radiolog & iacute; aa cirujanos en hospitales de campa & ntilde; a, gracias a los dispositivos port & aacute; tiles dise & ntilde; ados por su madre, Marie Curie. Pero ella quedarse en Barleduc se convertirá en una lucha para ganarse el respeto de los soldados e incluso del resto del personal de la guardería y el infierno; Y, de repente, estalla la batalla. Alemania bombardea a Verdun, y luego todo será una carrera contra el tiempo para quitar la mayor cantidad de vidas posible de la muerte. Junto con Berthe y Shirley, Ir & egrave; ne se enfrentará al infierno durante la batalla más sangrienta y prolongada de la guerra. Y no solo lucharán por su propia supervivencia. El cielo y la tierra arden ... y están en medio de la batalla. span style = "vertical-align: heredar;"> Llenas de conciencia y feminidad y escritas en una prosa vibrante y literaria, las Batallas silenciadas nos muestran la Batalla de Verdún como nunca antes la hab & iacute; amos visto. Nieves Mu & ntilde; oz describe las vidas de todos los que participaron, porque no solo los soldados estaban todos & iacute ;, y todos podemos verlos y sentirlos: desde las trincheras, en las aldeas, en el aire, en los hospitales de campa & ntilde; a ... Porque como, En cualquier guerra, hubo vencedores y perdedores, pero todos ten & iacute; an un alma, y ​​en esta primera novela Nieves Mu & ntilde; oz abre su propio molde y lo transfiere a sus personajes para darnos un bien eterno: la esperanza. Llenas de conciencia y feminidad y escritas en una prosa vibrante y literaria, las Batallas silenciadas nos muestran la Batalla de Verdún como nunca antes la hab & iacute; amos visto. Nieves Mu & ntilde; oz describe las vidas de todos los que participaron, porque no solo los soldados estaban todos & iacute ;, y todos podemos verlos y sentirlos: desde las trincheras, en las aldeas, en el aire, en los hospitales de campa & ntilde; a ... Porque como, En cualquier guerra, hubo vencedores y perdedores, pero todos ten & iacute; an un alma, y ​​en esta primera novela Nieves Mu & ntilde; oz abre su propio molde y lo transfiere a sus personajes para darnos un bien eterno: la esperanza. Llenas de conciencia y feminidad y escritas en una prosa vibrante y literaria, las Batallas silenciadas nos muestran la Batalla de Verdún como nunca antes la hab & iacute; amos visto. Nieves Mu & ntilde; oz describe las vidas de todos los que participaron, porque no solo los soldados estaban todos & iacute ;, y todos podemos verlos y sentirlos: desde las trincheras, en las aldeas, en el aire, en los hospitales de campa & ntilde; a ... Porque como, En cualquier guerra, hubo vencedores y perdedores, pero todos ten & iacute; an un alma, y ​​en esta primera novela Nieves Mu & ntilde; oz abre su propio molde y lo transfiere a sus personajes para darnos un bien eterno: la esperanza.

      • Adventure
        July 2020

        The Wandering Earth

        by Liu Cixin, Zhou You, Yang Guang, Peng Fang

        It was picture and popular science book, adapted form the same name’s fiction. The author, Liu Cixin, is the best famous popular science fiction author who had obtained Hugo Award, the science fiction achievement award like Nobel Prize. The works painted the sun will become red giant star so that to destroyed all solar system’s plants including the Earth. So people launched great plan to let the Earth to depart away from solar system. A quarter of the title after text was popular science article about concerning physics with lots of picture, which let readers visually and subtly understood geosciences, Astrophysical Sciences, and so on , after reading the science fiction.

      • December 2012

        DefrICtion

        by Chris Potts

        Michael is CEO of a $64 billion global corporation, driving a strategy founded on productivity and growth. Despite having 'best practices' in place, spearheaded by Finance, he's convinced that many of the company's investments in change are still not delivering the most value they can, or even the value they promised. Late one night, while reading a hard-to-believe Business Case for an IT transformation, he makes it his business to find out why. With the help of his inner-circle of trusted executives and managers, and the serendipitous appearance of a friend-of-a-friend, Michael discovers what's been missing all along in the Boardroom, the businesses, and the company culture. He is faced with deciding what it's worth to sort things out, once and for all, with a strategy that combines Enterprise Architecture with Investing in Change. In this conclusion to the trilogy that began with FruITion and continued with RecrEation, Michael finds that the consequences for everyone are part cultural, part structural, and part operational. They mean challenging some of the orthodoxies that were supposed to solve the problem but have made things worse instead. What will he choose to do? About Chris Potts: Chris Potts is a corporate strategist and executive mentor, who works with people around the world growing the value they deliver through investing in change and IT.

      • Computer science
        October 2011

        Data Modeling Made Simple with PowerDesigner

        by Steve Hoberman, George McGeachie

        Data Modeling Made Simple with PowerDesigner will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices, and how to apply these principles with PowerDesigner.   Hear one of the authors, Steve Hoberman, talk about this book.   You'll build many PowerDesigner data models along the way, increasing your skills first with the fundamentals and later with more advanced feature of PowerDesigner. This book combines real-world experience and best practices to help you master the following ten objectives:   This book has ten key objectives for you, the reader: You will know when a data model is needed and which PowerDesigner models are the most appropriate for each situation You will be able to read a data model of any size and complexity with the same confidence as reading a book You will know when to apply and how to make use of all the key features of PowerDesigner You will be able to build, step-by-step in PowerDesigner, a pyramid of linked data models, including a conceptual data model, a fully normalized relational data model, a physical data model, and an easily navigable dimensional model You will be able to apply techniques such as indexing, transforms, and forward engineering to turn a logical data model into an efficient physical design You will improve data governance and modeling consistency within your organization by leveraging features such as PowerDesigner’s reference models, Glossary, domains, and model comparison and model mapping techniques You will know how to utilize dependencies and traceability links to assess the impact of change You will know how to integrate your PowerDesigner models with externally-managed files, including the import and export of data using Excel and Requirements documents You will know where you can take advantage of the entire PowerDesigner model set, to increase the success rate of corporate-wide initiatives such as business intelligence and enterprise resource planning (ERP) You will understand the key differentiators between PowerDesigner and other data modeling tools you may have used before

      • Computer science
        August 2012

        UML Requirements Modeling For Business Analysts

        by Norman Daoust

        Hear the author, Norman Daoust, talk about his book.   This book provides you with a collection of best practices, guidelines, and tips for using the Unified Modeling Language (UML) for business analysis. The contents have been assembled over the years based on experience and documented best practices. Over sixty easy to understand UML diagram examples will help you to apply these ideas immediately. If you use, expect to use, or think you should use the Unified Modeling Language (UML) or use cases in your business analysis activities, this book will help you: communicate more succinctly and effectively with your stakeholders including your software development team, increase the likelihood that your requirements will be reviewed and understood, reduce requirements analysis, documentation, and review time.   The first three chapters explain the reasons for utilizing the UML for business analysis, present a brief history of the UML and its diagram categories, and describe a set of general modeling guidelines and tips applicable to all of the UML diagram types. Each of the next thirteen chapters is dedicated to a different UML diagram type: Use Case Diagrams Activity Diagrams Interaction Overview Diagrams Class Diagrams Object Diagrams State Machine Diagrams Timing Diagrams Sequence Diagrams Communication Diagrams Composite Structure Diagrams Component Diagrams Deployment Diagrams Package Diagrams   The next two chapters explain additional diagram types that are important for business analysts and that can be created using UML notation: Context Diagrams using Communication diagram notation Data Models using Class diagram notation   These chapters are followed by a chapter that describes criteria for selecting the various diagram types. The final chapter presents a case study.   Norman Daoust is a business analyst trainer, requirements modeler, data modeler, healthcare electronic data exchange specialist, fretted instrument specialist, and organic gardener. He is the principal consultant for Daoust Associates, a company based in Cambridge, Massachusetts, United States. He specializes in business analyst training, information modeling, and healthcare systems data integration.

      • Business & management
        June 2014

        Data Modeling for MongoDB

        by Steve Hoberman

        Learn how to capture and precisely document business requirements to create an efficient MongoDB design. Watch Steve Hoberman talk about his book.   Congratulations! You completed the MongoDB application within the given tight timeframe and there is a party to celebrate your application’s release into production. Although people are congratulating you at the celebration, you are feeling some uneasiness inside. To complete the project on time required making a lot of assumptions about the data, such as what terms meant and how calculations are derived. In addition, the poor documentation about the application will be of limited use to the support team, and not investigating all of the inherent rules in the data may eventually lead to poorly-performing structures in the not-so-distant future.   Now, what if you had a time machine and could go back and read this book. You would learn that even NoSQL databases like MongoDB require some level of data modeling. Data modeling is the process of learning about the data, and regardless of technology, this process must be performed for a successful application. You would learn the value of conceptual, logical, and physical data modeling and how each stage increases our knowledge of the data and reduces assumptions and poor design decisions.   Read this book to learn how to do data modeling for MongoDB applications, and accomplish these five objectives: Understand how data modeling contributes to the process of learning about the data, and is, therefore, a required technique, even when the resulting database is not relational.  That is, NoSQL does not mean NoDataModeling! Know how NoSQL databases differ from traditional relational databases, and where MongoDB fits. Explore each MongoDB object and comprehend how each compares to their data modeling and traditional relational database counterparts, and learn the basics of adding, querying, updating, and deleting data in MongoDB. Practice a streamlined, template-driven approach to performing conceptual, logical, and physical data modeling. Recognize that data modeling does not always have to lead to traditional data models! Distinguish top-down from bottom-up development approaches and complete a top-down case study which ties all of the modeling techniques together.   This book is written for anyone who is working with, or will be working with MongoDB, including business analysts, data modelers, database administrators, developers, project managers, and data scientists. About the Author: Steve Hoberman is the most requested data modeling instructor in the world. He taught his first data modeling class in 1992 and has educated more than 10,000 people about data modeling and business intelligence techniques since then. Steve is the author of seven books on data modeling, the founder of the Design Challenges group, inventor of the Data Model Scorecard, Conference Chair of the Data Modeling Zone conference, and recipient of the 2012 Data Administration Management Association (DAMA) International Professional Achievement Award. Steve can be reached at me@stevehoberman.com, @DataMdlRockStar on Twitter, or through Steve Hoberman on Linked-In.

      • August 2012

        The Nimble Elephant

        by John Giles

        Hear the author, John Giles, talk about this book,   "Get it done well and get it done fast" are twin, apparently opposing, demands. Data architects are increasingly expected to deliver quality data models in challenging timeframes, and agile developers are increasingly expected to ensure that their solutions can be easily integrated with the data assets of the overall organization. If you need to deliver quality solutions despite exacting schedules, "The Nimble Elephant" will help by describing proven techniques that leverage the libraries of published data model patterns to rapidly assemble extensible and robust designs. The three sections in the book provide guidelines for applying the lessons to your own situation, so that you can apply the techniques and patterns immediately to your current assignments. The first section, Foundations for Data Agility, addresses some perceived aspects of friction between "data" and "agile" practitioners. As a starting point for resolving the differences, pattern levels of granularity are classified, and their interdependencies exposed. A context of various types of models is established (e.g. conceptual / logical / physical, and industry / enterprise / project), and you will learn how to customize patterns within specific model types. The second section, Steps Towards Data Agility, shares guidelines on generalizing and specializing, with cautions on the dangers of going too far. Creativity in using patterns beyond their intended purpose is encouraged. The short-term "You Ain't Gonna Need It" (YAGNI) philosophy of agile practitioners, and the longer-term strategic perspectives of architects, are compared and evaluated. Consideration is given to the potential of enterprise views contributing to project-specific models. Other topics include industry models, iterative modeling, creation of patterns when none exist, and patterns for rules-in-data. The section ends with a perspective on the modeler's possible role in agile projects, followed by a case study. The final section, A Bridge to the Land of Object Orientation, provides a pathway for re-skilling traditional data modelers who want to expand their options by actively engaging with the ranks of object-oriented developers. I'm delighted to see that John has put his extensive experience and broad knowledge of data modeling into print! John's ability to simplify the complex, and to share his knowledge and enthusiasm - and humor - with colleagues, comes through in this very useful and readable book. I recommend it to anyone working with data.

      • March 2013

        Data Modeling Made Simple with ER/Studio Data Architect

        by Steve Hoberman

        Hear the author, Steve Hoberman, talk about this book.   Data Modeling Made Simple with ER/Studio Data Architect will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices, along with how to apply these principles with ER/Studio. You'll build many ER/Studio data models along the way, applying best practices to master these ten objectives: You will know why a data model is needed and which ER/Studio models are the most appropriate for each situation You will be able to read a data model of any size and complexity with the same confidence as reading a book You will know how to apply all the key features of ER/Studio You will be able to build relational and dimensional conceptual, logical, and physical data models in ER/Studio You will be able to apply techniques such as indexing, transforms, and forward engineering to turn a logical data model into an efficient physical design You will improve data model quality and impact analysis results by leveraging ER/Studio’s lineage functionality and compare/merge utility You will achieve enterprise architecture through ER/Studio’s repository and portal functionality You will be able to apply ER/Studio’s data dictionary features You will learn ways of sharing the data model through reporting and through exporting the model in a variety of formats You will leverage ER/Studio’s naming functionality to improve naming consistency

      • Data warehousing
        February 2012

        Data and Reality

        A Timeless Perspective On Perceiving & Managing Information in Our Imprecise World -- 3rd Edition

        by William Kent

        Let's step back to the year 1978. Sony introduces hip portable music with the Walkman, Illinois Bell Company releases the first mobile phone, Space Invaders kicks off the video game craze, and William Kent writes Data and Reality. We have made amazing progress in the last four decades in terms of portable music, mobile communication, and entertainment, making devices such as the original Sony Walkman and suitcase-sized mobile phones museum pieces today. Yet remarkably, the book Data and Reality is just as relevant to the field of data management today as it was in 1978. Data and Reality gracefully weaves the disciplines of psychology and philosophy with data management to create timeless takeaways on how we perceive and manage information. Although databases and related technology have come a long way since 1978, the process of eliciting business requirements and how we think about information remains constant. This book will provide valuable insights whether you are a 1970s data-processing expert or a modern-day business analyst, data modeler, database administrator, or data architect.This third edition of Data and Reality differs substantially from the first and second editions. Data modeling thought leader Steve Hoberman has updated many of the original examples and references and added his commentary throughout the book, including key points at the end of each chapter. The important takeaways in this book are rich with insight yet presented in a conversational writing style. Here are just a few of the issues this book tackles:Has "business intelligence" replaced "artificial intelligence"?Why is a map's geographic landscape analogous to a data model's information landscape?Where do forward and reverse engineering fit in our thought process?Why are we all becoming "data archeologists"?What causes the communication chasm between the business professional and the information technology professional, and how can the logical data model bridge this gap?Why do we invest in hardware and software to solve business problems before determining what the business problems are in the first place?What is the difference between oneness, sameness, and categories?Why does context play a role in every design decision?Why do the more important attributes become entities or relationships?Why do symbols speak louder than words?What's the difference between a data modeler, a philosopher, and an artist?Why is the 1975 dream of mapping all attributes still a dream today?What influence does language have on our perception of reality? Can we distinguish between naming and describing?From Graeme Simsion's foreword:While such fundamental issues remain unrecognized and unanswered, Data and Reality, with its lucid and compelling elucidation of the questions, needs to remain in print. I read the book as a database administrator in 1980, as a researcher in 2002, and just recently as the manuscript for the present edition. On each occasion I found something more, and on each occasion I considered it the most important book I had read on data modeling. It has been on my recommended reading list forever. The first chapter in particular should be mandatory reading for anyone involved in data modeling. In publishing this new edition, Steve Hoberman has not only ensured that one of the key books in the data modeling canon remains in print, but has added his own comments and up-to-date examples, which are likely to be helpful to those who have come to data modeling more recently. Don't do any more data modeling work until you've read it. About William: William Kent (1936-2005) was a renowned researcher in the field of data modeling. Author of Data and Reality, he wrote scores of papers and spoke at conferences worldwide, posing questions about database design and the management of information that remain unanswered today. Though he earned a bachelor's degree in chemical engineering and a master's in mathematics, he had no formal training in computer science. Kent worked at IBM and later at Hewlett-Packard Laboratories, where he helped develop prototype database systems. He also served on or chaired several international standards committees. Kent lived in New York City and later Menlo Park, Calif., before retiring to Moab, Utah, to pursue his passions of outdoor photography and protecting the environment. About Steve: Steve is currently a data modeling consultant and instructor. He taught his first data modeling class in 1992 and has educated more than 10,000 people about data modeling and business intelligence techniques since then. Steve balances the formality and precision of data modeling with the realities of building software systems with severe time, budget, and people constraints. In his consulting and teaching, he focuses on templates, tools, and guidelines to reap the benefits of data modeling with minimal investment. Steve is the author of five books on data modeling, the founder of the Design Challenges group, and inventor of the Data Model Scorecard.

      • Databases
        October 2009

        Data Modeling Made Simple

        A Practical Guide for Business and It Professionals

        by Steve Hoberman

        Hear the author, Steve Hoberman, talk about his book.   Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives: Know when a data model is needed and which type of data model is most effective for each situation Read a data model of any size and complexity with the same confidence as reading a book Build a fully normalized relational data model, as well as an easily navigatable dimensional model Apply techniques to turn a logical data model into an efficient physical design Leverage several templates to make requirements gathering more efficient and accurate Explain all ten categories of the Data Model Scorecard Learn strategies to improve your working relationships with others Appreciate the impact unstructured data has, and will have, on our data modeling deliverables Learn basic UML concepts Put data modeling in context with XML, metadata, and agile development

      • Cultural studies

        Many Cultures, One Team

        Build Your Cultural Repertoire

        by Catherine Mercer Bing

        Many Cultures, One Team is an essential aid for anyone who leads, is a member of, consults with, or supports global teams.  Starting from the premise that the concept of team is culturally bound, Catherine Mercer Bing provides guidance for improving team function and performance. Drawing on her extensive experience in supporting global teams, she challenges team leaders and members to reflect on their cultural assumptions - to improve their cultural metacognition - and provides key advice concerning engagement, productivity, and human process interactions on teams. Global competition is fierce, and the timeframe within which businesses maintain their competitive advantage is now counted in months rather than years. One important source of competitive advantage is human behavior. Team leaders that manage the subtle, but powerful, forces of group dynamics and culture achieve better business outcomes. Team leaders that fail to identify and manage these subtle forces in real-time risk having their plans thwarted. "Many Cultures, One Team" is based on Cass Mercer Bing's extensive experience helping virtual and multi-cultural teams achieve their full potential. "Many Cultures, One Team" provides extensive advice for team leaders and consultants in a ready-to-use format. It is a crucial guide to anyone who wishes to gain a better handle on a crucial source of competitive advantage: human dynamics on global and virtual teams. Dr. Amitai Touval, Zicklin School of Business My favorite part is the case box.  It raises questions and makes me think, 'darn, I don’t really know!'... The explanations tend to give me a 'Yes, yes, I know' feeling. Gert Jan Hofstede, Associate Professor at Wageningen UR, The Netherlands Cass has presented a framework for global leaders to go beyond their own comfort zone allowing leaders to recognize and appreciate the cultural challenges involved in leading cross cultural teams. The leader is able to recognize and identify the cultural dynamics and utilize these techniques and strategies in making the organization function more effectively. This approach and the techniques outlined can be applied at multiple levels in the organization which makes a compelling case for leaders and HR professionals who operate in the complex network of cultural behavioral preferences present in global teams. John E. Warren III, Global Human Resources Executive

      • Computer science
        April 2009

        Data Modeling for the Business

        A Handbook for Aligning the Business With It Using High-level Data Models

        by Steve Hoberman, Donna Burbank, Chris Bradley

        Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach and hands-on exercises to help you practice topics on your own.   Hear one of the authors, Steve Hoberman, talk about this book.   In this book, we review data modeling basics and explain why the core concepts stored in a high-level data model can have significant business impact on an organization. We explain the technical notation used for a data model and walk through some simple examples of building a high-level data model.  We also describe how data models relate to other key initiatives you may have heard of or may be implementing in your organization.   This book contains best practices for implementing a high-level data model, along with some easy-to-use templates and guidelines for a step-by-step approach.  Each step will be illustrated using many examples based on actual projects we have worked on. Names have been changed to protect the innocent, but the pain points and lessons have been preserved. One example spans an entire chapter and will allow you to practice building a high-level data model from beginning to end, and then compare your results to ours. Building a high-level data model following the ten step approach you’ll read about is a great way to ensure you will retain the new skills you learn in this book.   As is the case in many disciplines, using the right tool for the right job is critical to the overall success of your high-level data model implementation.  To help you in your tool selection process, there are several chapters dedicated to discussing what to look for in a high-level data modeling tool and a framework for choosing a data modeling tool, in general.    This book concludes with a real-world case study that shows how an international energy company successfully used a high-level data model to streamline their information management practices and increase communication throughout the organization—between both businesspeople and IT.   One of the most critical systems issues is aligning business with IT and fulfilling business needs using data models. The authors of Data Modeling for the Business do a masterful job at simply and clearly describing the art of using data models to communicate with business representatives and meet business needs. The book provides many valuable tools, analogies, and step-by-step methods for effective data modeling and is an important contribution in bridging the much needed connection between data modeling and realizing business requirements. Len Silverston, author of The Data Model Resource Book series

      • Thriller / suspense
        September 2011

        The Hidden Corporation

        A Data Management Security Novel

        by David Schlesinger, CISSP

        If you wonder why good companies lose lots of personal information, and are not sure if your company is immune from this disaster, this insightful book shines a bright light on the hidden processes in most companies where data governance and information security are usually absent. These gaps are often the root cause of sensitive data loss. Follow cybersecurity specialist Nancy MacBaron who fights in the corporate trenches against criminal hackers intent on stealing her company's sensitive information, yet discovers hidden data security gaps in her corporation while investigating a data theft. The world's first data security business novel is an accessible way to illuminate hidden data dangers while explaining some of the cybersecurity challenges of today. Called into her boss's office early one morning, Nancy MacBaron is given dual assignments: one, to help locate the person who is holding their data for ransom, and two, investigate how their information management process allowed such a huge amount of sensitive information to be stolen. Amidst the rivalry among departments, and the pressure of financial disaster for the company, Nancy begins a journey of discovery that shows her a landscape of data process activity that nobody is coordinating or even really aware exists. Nancy confers with a number of people, some helpful, some resentful of outsiders, all adding more pieces to the puzzle. Amidst the new ideas, old work habits, and personal conflicts Nancy begins to recognize hidden and ungoverned gaps within the corporation along with following clues to find the criminal before the company's data is auctioned off to the highest bidder. Follow Nancy as she gathers different perspectives from developers, data architects, managers, attorneys, cybersecurity specialists, data governance groups, law enforcement, and members of her own family to formulate a method to protect sensitive information that coordinates the expertise of many business groups to eliminate gaps in The Hidden Corporation. David Schlesinger has 25 years of experience in information technology and data security management. He is CISSP certified in cybersecurity and is on the Board of Directors of the Phoenix ISSA, a security professional association. David has authored two US Patents for data governance methods that use Metadata classifications to audit and automate user rights and regulatory compliance, and speaks widely at data management and security conferences. He is a Senior Security Architect and currently consults with commercial and government organizations on information protection involving enhanced Metadata, self-aware data architecture, data classification practices, and information regulatory compliance.

      • Business & management
        January 2011

        Enterprise Model Patterns

        Describing the World

        by David C. Hay

        Hear the author, David Hay, talk about this book.   This book teaches you how to capture and communicate both the abstract and concrete building blocks of your organization’s data, in order to provide a coherent and comprehensive foundation for systems development. “This book presents the most comprehensive treatment of high-level abstractions I've seen. Any event, business, and/or systems analyst should have this book available, both as a learning text and as an indispensible reference book. The knowledge packed away in this book takes decades to acquire and gestate. We are all fortunate to have it in a single volume.”James OdellCo-chair, OMG - Analysis and Design "UML and SoaML" Task Force "David addresses a key, difficult, challenge for data modelling (and ontology) in this book - extracting the common pattern that underlies and unifies the variety of real data models that people use. And, what is almost as important to many readers, he does this in a clear and understandable way."Chris PartridgeChief Ontologist, The BORO Centre "A great data model, one that lays the essence of a business bare, is a thing of beauty. It simplifies process, eases communication, and brings order to chaos. A great data model serves for a lifetime. Powerful stuff, this."Tom Redman, PresidentNavesink Consulting Group, LLC "Finally, choosing a level of abstraction for a data model is addressed methodically. David should be applauded for grasping this thorny issue and producing a wonderfully readable book. Every data modeler should have one".Cliff Longman, PresidentAdaptable Data In 1995, David Hay published Data Model Patterns: Conventions of Thought - the groundbreaking book on how to use standard data models to describe the standard business situations. Enterprise Model Patterns: Describing the World builds on the concepts presented there, adds 15 years of practical experience, and presents a more comprehensive view. This model addresses your enterprise via four levels of abstraction: Level 0: An abstract template that underlies the Level 1 model, plus two meta models: Information Resources and Accounting. Each of these itself represents the rest of the enterprise, so to model it is to “model a model”, so to speak. Level 1: An enterprise model that is generic enough to apply to any company or government agency, but concrete enough to be readily understood by all. It describes people and organizations, geographic locations, (physical) assets, activities, and time. Level 2: A more detailed model describing specific functional areas: facilities and other addresses, human resources, communications and marketing, contracts, manufacturing, and the laboratory. Level 3: Examples of the details that can be added to a model to address what is truly unique in a particular industry. Here you see how to address the unique bits in areas as diverse as criminal justice, microbiology, banking, oil field production, and highway maintenance.

      • Computer science
        August 2011

        Data Modeling Made Simple with CA ERwin Data Modeler r8

        With Ca Erwin Data Modeler R8

        by Donna Burbank, Steve Hoberman

        Hear one of the authors, Steve Hoberman, talk about this book.   Data Modeling Made Simple with CA ERwin Data Modeler r8 will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices, and how to apply these principles with CA ERwin Data Modeler r8. You’ll build many CA ERwin data models along the way, mastering first the fundamentals and later in the book the more advanced features of CA ERwin Data Modeler. This book combines real-world experience and best practices with down to earth advice, humor, and even cartoons to help you master the following ten objectives: Understand the basics of data modeling and relational theory, and how to apply these skills using CA ERwin Data Modeler Read a data model of any size and complexity with the same confidence as reading a book Understand the difference between conceptual, logical, and physical models, and how to effectively build these models using CA ERwin’s Data Modelers Design Layer Architecture Apply techniques to turn a logical data model into an efficient physical design and vice-versa through forward and reverse engineering, for both ‘top down’ and bottom-up design Learn how to create reusable domains, naming standards, UDPs, and model templates in CA ERwin Data Modeler to reduce modeling time, improve data quality, and increase enterprise consistency Share data model information with various audiences using model formatting and layout techniques, reporting, and metadata exchange Use the new workspace customization features in CA ERwin Data Modeler r8 to create a workflow suited to your own individual needs Leverage the new Bulk Editing features in CA ERwin Data Modeler r8 for mass metadata updates, as well as import/export with Microsoft Excel Compare and merge model changes using CA ERwin Data Modelers Complete Compare features Optimize the organization and layout of your data models through the use of Subject Areas, Diagrams, Display Themes, and more

      • October 2012

        Connecting the Data

        by Angelo R. Bobak

        Business data integration is a complex problem that must be solved when organizations change or enhance their internal structures. The goal of this book is to present a simple yet thorough resource that describes the challenges of business data integration and the solutions to these challenges such as schema integration, illustrated through an Operational Data Store (ODS) case study. This book contains three sections spanning ten chapters. Section I, Foundational Concepts, will provide you with the necessary basic concepts and discuss schema integration. Section II, Preparation and Design, introduces the case study and we will reverse engineer each of the data sources to create a set of data dictionary reports which will provide us with the meta data we need to apply the schema integration process. Section III, Physical Implementation, will present scripts to populate each of the source databases and spreadsheets and use reports to create Extract, Transform, and Load (ETL) specifications. The ten chapters within these three sections are: Chapter 1 – Introduction and Roadmap Chapter 2 – What is an Operational Data Store (ODS)? Chapter 3 – What is Schema Integration? Chapter 4 – The Role of the ODS within DW Architectures Chapter 5 – Reverse Engineering the four Source Schema Chapter 6 – Designing the Interim Schema Chapter 7 – Preparing the ETL Specifications Chapter 8 – Designing the Physical ODS Database Model Chapter 9 – Designing Our ETL processes with SSIS Chapter 10 – Data Quality Profiling Angelo Bobak currently holds the position of Director of Data Architecture for an international ITIL services company. He holds a Masters in Computer Science and Bachelor of Electrical Engineering degrees. He has written several books on data modeling and distributed database architectures. Angelo lives in New York with his wife Cathy.

      • Management & management techniques
        October 2010

        How Work Gets Done

        Business Process Management, Basics & Beyond

        by Artie Mahal

        Hear the author, Artie Mahal, talk about his book.   Rediscover how your organization works and where it can be improved by using simple, yet powerful techniques!   How Work Gets Done will provide the business or IT professional with a practical working knowledge of Business Process Management (BPM). This book is written in a conversational style that encourages you to read it from start to finish and master these objectives: Learn how to identify the goals and drivers important to your organization and how to align these with key performance measures Understand how business strategies, business policies, and operational procedures need to be connected within a Business Process Architecture Know the basic building blocks of any business process - Inputs, Outputs, Guides, and Enablers Learn how to create a BPM Center of Excellence in your organization Acquire the skills to establish a BPM methodology addressing Enterprise-level, Process-Level, and Implementation-Level priorities Learn how to build a Process Competency Framework encompassing all BPM stakeholders Obtain the knowledge to improve a process step-by-step with easy to use techniques and templates such as swimlanes and flowcharts   How Work Gets Done is a clear, concise, and well-navigated journey into the world of Business Processes and Business Process Management. From a practical introduction through advanced topics around methodology and competencies, it is suitable for business process newcomers and seasoned practitioners alike. It should be required reading at all levels of every organization. Eugene Fucetola - Global Application Messaging and Integration, Operations Manager, Mars Information Services   If you have always wished you had a very practical friend who could sit down and talk you through just what is involved improving how work gets done at your organization, this is the book! Paul Harmon - Executive Editor, Business Process Trends and Chief Methodologist, BPTrends Associates   Artie Mahal has done something that was thought to be impossible - produce an easily readable book about business process management. He paints pictures with words, offers many easy-to-grasp analogies, and stimulates with simplifying charts of complex concepts. Leon Fraser- Lecturer, Rutgers Business School Chapter Listing: Chapter 1 - Enterprise Business Model Chapter 2 - Business Process Hierarchy Chapter 3 - Business Process Blueprint Chapter 4 - Anatomy of a Process Chapter 5 - Process Knowledge Chapter 6 - Business Models Chapter 7 - Process Configuration Chapter 8 - BPM Methodology Chapter 9 - BPM Competencies Chapter 10 - BPM Services Chapter 11 - Software Tools Chapter 12 - NewAge Foods Business Process Case Study

      • Language teaching & learning (other than ELT)
        October 2020

        Ready for Reading Success 1: Develop Your Reading Comprehension Skills

        by Owain Mckimm

        Ready for Reading Success is a four-volume series of exercise books designed for beginners which aims to develop reading competence and improve reading skills. As 12-year basic education emphasizes the importance of interdisciplinary and real-life-based learning, this series is designed to meet those objectives. The book contains 50 articles that come in many different forms, including passages, poems, dialogues, advertisements, etc. Each text is composed of no more than 150 words, and is followed by five multiple-choice comprehension questions that help train readers’ acquisition ability and allow self-examination. The book is divided into four primary units, within which are subunits that focus on different skills. Topics in this book includes literature, food, plants, culture, and travel, to name but a few. With all its merits, the book serves as an incomparable tool that empowers readers to soar to success. Structure Unit 1: Reading Skills 1-1 Subject Matter / Main Idea 1-2 Supporting Details / Cause & Effect 1-3 Fact Or Opinion / Making Inferences 1-4 Review: Reading Skills This unit covers six key ideas to look for when reading an article. In this unit, readers will learn to recognize what a text is mainly about, understand how an author feels about a topic, make assumptions based on information, and observe how details can be used to support main ideas. Unit 2: Word Study Synonyms / Antonyms / Words In Context In this unit, you will practice identifying words with the same or opposite meanings, and guessing the meanings of words from their context. These skills will help you understand new vocabulary and build vocabulary on your own in the future. Unit 3: Study Strategies 3-1 Visual Materials 3-2 Reference Sources Visual material like charts and graphs, and reference sources like indexes and dictionaries, all provide important information. What’s more, they help you understand complicated information more quickly than you can by reading. In this unit, you will learn to use them to gather information. Unit 4: Final Review 4-1 Review: Reading Skills 4-2 Review: Word Study 4-3 Review: Visual Material 4-4 Review: Reference Sources In this unit, you will review what you have learned. From these comprehensive questions, you can examine how well you have absorbed the ideas and material in this book.

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