Developing High Quality Data Models

Developing High Quality Data Models
Author: Matthew West
Publsiher: Elsevier
Total Pages: 408
Release: 2011-02-07
ISBN 10: 9780123751072
ISBN 13: 0123751071
Language: EN, FR, DE, ES & NL

Developing High Quality Data Models Book Review:

Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models. The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool. This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling. Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates Develops ideas for creating consistent approaches to high quality data models

Developing High Quality Data Models

Developing High Quality Data Models
Author: Matthew West
Publsiher: Morgan Kaufmann Pub
Total Pages: 389
Release: 2011
ISBN 10: 9780123751065
ISBN 13: 0123751063
Language: EN, FR, DE, ES & NL

Developing High Quality Data Models Book Review:

Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models. The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool. This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling. * Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality *Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates *Develops ideas for creating consistent approaches to high quality data models

The Data Modeling Handbook

The Data Modeling Handbook
Author: Michael C. Reingruber,William W. Gregory
Publsiher: John Wiley & Sons Incorporated
Total Pages: 362
Release: 1994-12-17
ISBN 10:
ISBN 13: UCSD:31822018846469
Language: EN, FR, DE, ES & NL

The Data Modeling Handbook Book Review:

This practical, field-tested reference doesn't just explain the characteristics of finished, high-quality data models--it shows readers exactly how to build one. It presents rules and best practices in several notations, including IDEFIX, Martin, Chen, and Finkelstein. The book offers dozens of real-world examples and go beyond basic theory to provide users with practical guidance.

Data Modeling for the Business

Data Modeling for the Business
Author: Steve Hoberman,Donna Burbank,Chris Bradley
Publsiher: Technics Publications
Total Pages: 288
Release: 2009-04-01
ISBN 10: 1634620437
ISBN 13: 9781634620437
Language: EN, FR, DE, ES & NL

Data Modeling for the Business Book Review:

Did you ever try getting Businesspeople and IT to agree on the project scope for a new application? Or try getting Marketing and Sales to agree on the target audience? Or try bringing new team members up to speed on the hundreds of tables in your data warehouse — without them dozing off? Whether you are a businessperson or an IT professional, you can be the hero in each of these and hundreds of other scenarios by building a High-Level Data Model. The High-Level Data Model is a simplified view of our complex environment. It can be a powerful communication tool of the key concepts within our application development projects, business intelligence and master data management programs, and all enterprise and industry initiatives. 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. 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. Data modeling is one of the under-exploited, and potentially very valuable, business capabilities that are often hidden away in an organization’s Information Technology department. Data Modeling for the Business highlights both the resulting damage to business value, and the opportunities to make things better. As an easy-to follow and comprehensive guide on the ‘why’ and ‘how’ of data modeling, it also reminds us that a successful strategy for exploiting IT depends at least as much on the information as the technology. Chris Potts, Corporate IT Strategist and Author of fruITion: Creating the Ultimate Corporate Strategy for Information Technology 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

Data Modeling Essentials

Data Modeling Essentials
Author: Graeme Simsion,Graham Witt
Publsiher: Elsevier
Total Pages: 560
Release: 2004-12-03
ISBN 10: 9780080488677
ISBN 13: 0080488676
Language: EN, FR, DE, ES & NL

Data Modeling Essentials Book Review:

Data Modeling Essentials, Third Edition, covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with "the rules". In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises. This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective. Thorough coverage of the fundamentals and relevant theory. Recognition and support for the creative side of the process. Expanded coverage of applied data modeling includes new chapters on logical and physical database design. New material describing a powerful technique for model verification. Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict.

Data Modeling Essentials

Data Modeling Essentials
Author: Graeme Simsion,Graham Witt,Matthew West
Publsiher: Newnes
Total Pages: 600
Release: 2015-03-29
ISBN 10: 9780123965394
ISBN 13: 012396539X
Language: EN, FR, DE, ES & NL

Data Modeling Essentials Book Review:

If you are seeking expert tutelage for data modelling tools and techniques, you need look no further. Regardless of your level of expertise, as a data analyst, data modeler, data architect, database designer, database application developer, database administrator, business analysts, or systems designers, this book will serve as an invaluable resource in your effort to build reliable and effective data models. Beginning with the basics, this book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modelling and database design. Later chapters delve into advanced topics and enterprise data modelling, covering business rules, data warehousing, data migration, and more. This new and expanded edition updates existing content where current practice dictates and adds new content on Modelling XML, Master and Reference Data, Mapping Between Models, Data Migration, and other areas of intense interest to the data modelling community. NEW TO THIS EDITION • Enhanced contextual treatment of data modeling by providing more examples of data models and their quality in examining where the benefits derive. • NEW chapter on Master and Reference Data Management • NEW chapter of Data Migration • NEW chapter on modeling XML messages • NEW chapter on Mapping Between Data Models The perfect balance of theory and practice giving you both the foundation and the tools to develop high quality data models. Perfect reference for the reflective practitioner providing clear and accessible guidance to data modeling techniques. An invaluable resource containing vast amounts of useful and well illustrated information to those involved in data modeling, from the novice to the expert.

Data Model Patterns

Data Model Patterns
Author: David Hay
Publsiher: Addison-Wesley
Total Pages: 288
Release: 2013-07-18
ISBN 10: 0133488624
ISBN 13: 9780133488623
Language: EN, FR, DE, ES & NL

Data Model Patterns Book Review:

This is the digital version of the printed book (Copyright © 1996). Learning the basics of a modeling technique is not the same as learning how to use and apply it. To develop a data model of an organization is to gain insights into its nature that do not come easily. Indeed, analysts are often expected to understand subtleties of an organization's structure that may have evaded people who have worked there for years. Here's help for those analysts who have learned the basics of data modeling (or "entity/relationship modeling") but who need to obtain the insights required to prepare a good model of a real business. Structures common to many types of business are analyzed in areas such as accounting, material requirements planning, process manufacturing, contracts, laboratories, and documents. In each chapter, high-level data models are drawn from the following business areas: The Enterprise and Its World The Things of the Enterprise Procedures and Activities Contracts Accounting The Laboratory Material Requirements Planning Process Manufacturing Documents Lower-Level Conventions

The Data Model Resource Book Volume 1

The Data Model Resource Book  Volume 1
Author: Len Silverston
Publsiher: John Wiley & Sons
Total Pages: 560
Release: 2011-08-08
ISBN 10: 111808232X
ISBN 13: 9781118082324
Language: EN, FR, DE, ES & NL

The Data Model Resource Book Volume 1 Book Review:

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.

Data Modeling for Quality

Data Modeling for Quality
Author: Graham Witt
Publsiher: Technics Publications
Total Pages: 304
Release: 2021-01-19
ISBN 10: 1634629159
ISBN 13: 9781634629157
Language: EN, FR, DE, ES & NL

Data Modeling for Quality Book Review:

This book is for all data modelers, data architects, and database designers―be they novices who want to learn what’s involved in data modeling, or experienced modelers who want to brush up their skills. A novice will not only gain an overview of data modeling, they will also learn how to follow the data modeling process, including the activities required for each step. The experienced practitioner will discover (or rediscover) techniques to ensure that data models accurately reflect business requirements. This book describes rigorous yet easily implemented approaches to: · modeling of business information requirements for review by business stakeholders before development of the logical data model · normalizing data, based on simple questions rather than the formal definitions which many modelers find intimidating · naming and defining concepts and attributes · modeling of time-variant data · documenting business rules governing both the real world and data · data modeling in an Agile project · managing data model change in any type of project · transforming a business information model to a logical data model against which developers can code · implementing the logical data model in a traditional relational DBMS, an SQL:2003-compliant DBMS, an object-relational DBMS, or in XML. Part 1 describes business information models in-depth, including: · the importance of modeling business information requirements before embarking on a logical data model · business concepts (entity classes) · attributes of business concepts · attribute classes as an alternative to DBMS data types · relationships between business concepts · time-variant data · generalization and specialization of business concepts · naming and defining the components of the business information model · business rules governing data, including a distinction between real-world rules and data rules. Part 2 journeys from requirements to a working data resource, covering: · sourcing data requirements · developing the business information model · communicating it to business stakeholders for review, both as diagrams and verbally · managing data model change · transforming the business information model into a logical data model of stored data for implementation in a relational or object-relational DBMS · attribute value representation and data constraints (important but often overlooked) · modeling data vault, dimensional and XML data.

The Enterprise Data Model

The Enterprise Data Model
Author: Andy Graham
Publsiher: Koios Associates Limited
Total Pages: 160
Release: 2012-05
ISBN 10: 9780956582911
ISBN 13: 0956582915
Language: EN, FR, DE, ES & NL

The Enterprise Data Model Book Review:

Wouldn't it be great to understand all the data in your organisation? Just imagine being able to define, agree and manage information concepts that impact on business strategy? Then image that these information concepts can be linked to the physical database attributes that ultimately are used to create them. That's what this book is about. It focuses on the data model as the foundation for achieving this understanding. This book provides a framework for the enterprise data model, the business reasons behind it and the differences between conceptual, logical and physical data models. The question of how, and why, to use a data model artifact as part of the data governance toolkit for the whole enterprise is also addressed. This publication is not an in-depth manual on how to model data for a new database system or your next design project. It instead focuses at a level above these implementation projects and addresses the issues that organisations typical struggling with such as: * How do we provide a framework within which we can manage our data assets? * How do we develop applications that adhere to a set of data standards; without creating a nightmare of administration and governance that is both unwieldy and unusable? * How can we get business value from our enterprise data? Chapter headings are: * Chapter 1 - Introduction * Chapter 2 - Information and Data * Chapter 3 - Pillars of Value * Chapter 4 - An Overview of Data Modelling * Chapter 5 - Data Architecture * Chapter 6 - The Enterprise Data Model * Chapter 7 - Build the Model one Project at a Time * Chapter 8 - Master Data * Chapter 9 - Data Governance * Chapter 10 - The Enterprise Data Framework This 2nd edition revises the original text to add extra details around key areas such as the enterprise data model framework and the pillars of value. It also improves the quality of the original text.

Exam Ref 70 768 Developing SQL Data Models

Exam Ref 70 768 Developing SQL Data Models
Author: Stacia Varga
Publsiher: Microsoft Press
Total Pages: 400
Release: 2017-05-05
ISBN 10: 1509305165
ISBN 13: 9781509305162
Language: EN, FR, DE, ES & NL

Exam Ref 70 768 Developing SQL Data Models Book Review:

Prepare for Microsoft Exam 70-768–and help demonstrate your real-world mastery of Business Intelligence (BI) solutions development with SQL Server 2016 Analysis Services (SSAS), including modeling and queries. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: • Design a multidimensional BI semantic model • Design a tabular BI semantic model • Develop queries using Multidimensional Expressions (MDX) and Data Analysis Expressions (DAX) • Configure and maintain SSAS This Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you are a database or BI professional with experience creating models, writing MDX or DAX queries, and using SSAS

Data Modeling Fundamentals

Data Modeling Fundamentals
Author: Paulraj Ponniah
Publsiher: John Wiley & Sons
Total Pages: 464
Release: 2007-06-30
ISBN 10: 9780470141014
ISBN 13: 0470141018
Language: EN, FR, DE, ES & NL

Data Modeling Fundamentals Book Review:

The purpose of this book is to provide a practical approach for IT professionals to acquire the necessary knowledge and expertise in data modeling to function effectively. It begins with an overview of basic data modeling concepts, introduces the methods and techniques, provides a comprehensive case study to present the details of the data model components, covers the implementation of the data model with emphasis on quality components, and concludes with a presentation of a realistic approach to data modeling. It clearly describes how a generic data model is created to represent truly the enterprise information requirements.

The Data Model Resource Book

The Data Model Resource Book
Author: Len Silverston,Paul Agnew
Publsiher: John Wiley & Sons
Total Pages: 648
Release: 2009-01-09
ISBN 10: 0470178450
ISBN 13: 9780470178454
Language: EN, FR, DE, ES & NL

The Data Model Resource Book Book Review:

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." —Bill Inmon, World-renowned expert, speaker, and author on data warehousing and widely recognized as the "father of data warehousing" "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 d

Patterns of Data Modeling

Patterns of Data Modeling
Author: Michael Blaha
Publsiher: CRC Press
Total Pages: 261
Release: 2010-06-01
ISBN 10: 9781439819906
ISBN 13: 1439819904
Language: EN, FR, DE, ES & NL

Patterns of Data Modeling Book Review:

Best-selling author and database expert with more than 25 years of experience modeling application and enterprise data, Dr. Michael Blaha provides tried and tested data model patterns, to help readers avoid common modeling mistakes and unnecessary frustration on their way to building effective data models. Unlike the typical methodology book, Patterns of Data Modeling provides advanced techniques for those who have mastered the basics. Recognizing that database representation sets the path for software, determines its flexibility, affects its quality, and influences whether it succeeds or fails, the text focuses on databases rather than programming. It is one of the first books to apply the popular patterns perspective to database systems and data models. It offers practical advice on the core aspects of applications and provides authoritative coverage of mathematical templates, antipatterns, archetypes, identity, canonical models, and relational database design.

Modelling Business Information

Modelling Business Information
Author: Keith Gordon
Publsiher: BCS, The Chartered Institute for IT
Total Pages: 202
Release: 2017-08-25
ISBN 10: 9781780173535
ISBN 13: 1780173539
Language: EN, FR, DE, ES & NL

Modelling Business Information Book Review:

This is an essential guide to entity relationship and class modelling for business analysts in line with, and beyond, the BCS Data Analysis syllabus.

Data Models and Analysis

Data  Models and Analysis
Author: Guoqi Han,Hai Lin,Douw Steyn
Publsiher: Routledge
Total Pages: 242
Release: 2019-02-01
ISBN 10: 1351691201
ISBN 13: 9781351691208
Language: EN, FR, DE, ES & NL

Data Models and Analysis Book Review:

This volume contains the ten most cited articles that have appeared in the journal Atmosphere-Ocean since 1995. These articles cover a wide range of topics in meteorology, climatology and oceanography. Modelling work is represented in five papers, covering global climate model development; a cumulus parameterization scheme for global climate models; development of a regional forecast modelling system and parameterization of peatland hydraulic processes for climate models. Data rehabilitation and compilation in order to support trend analysis work on comprehensive precipitation and temperature data sets is presented in four papers. Field studies are represented by a paper on the circumpolar lead system. While the modelling studies are global in their application and applicability, the data analysis and field study papers cover environments that are specifically, but not uniquely, Canadian. This book will be of interest to researchers, students and professionals in the various sub-fields of meteorology, oceanography and climate science.

Conceptual Modeling ER 98

Conceptual Modeling   ER  98
Author: Tok Wang Ling,Sudha Ram
Publsiher: Springer Science & Business Media
Total Pages: 482
Release: 1998-10-21
ISBN 10: 3540651896
ISBN 13: 9783540651895
Language: EN, FR, DE, ES & NL

Conceptual Modeling ER 98 Book Review:

This volume constitutes the refereed proceedings of the 17th International Conference on Conceptual Modeling, ER '98, held in Singapore, in November 1998. The 32 revised full papers presented were carefully reviewed and selected from a total of 95 submissions. The book is divided into chapters on conceptual modeling and design, user interface modeling, information retrieval on the Web, semantics and constraints, conceptual modeling tools, quality and reliability metrics, industrial experience in conceptual modeling, object-oriented database management systems, data warehousing, industrial case studies, object-oriented approaches.

Mastering Data Modeling

Mastering Data Modeling
Author: John Carlis
Publsiher: Addison-Wesley Professional
Total Pages: 329
Release: 2000-11-10
ISBN 10: 0134176537
ISBN 13: 9780134176536
Language: EN, FR, DE, ES & NL

Mastering Data Modeling Book Review:

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. Mastering Data Modeling 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. Assuming no prior knowledge, Mastering Data Modeling 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. 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.

High Performance Web Databases

High Performance Web Databases
Author: Sanjiv Purba
Publsiher: CRC Press
Total Pages: 832
Release: 2000-09-21
ISBN 10: 1420031562
ISBN 13: 9781420031560
Language: EN, FR, DE, ES & NL

High Performance Web Databases Book Review:

As Web-based systems and e-commerce carry businesses into the 21st century, databases are becoming workhorses that shoulder each and every online transaction. For organizations to have effective 24/7 Web operations, they need powerhouse databases that deliver at peak performance-all the time. High Performance Web Databases: Design, Development, and

Data Model Patterns A Metadata Map

Data Model Patterns  A Metadata Map
Author: David C. Hay
Publsiher: Elsevier
Total Pages: 432
Release: 2010-07-20
ISBN 10: 9780080477039
ISBN 13: 0080477038
Language: EN, FR, DE, ES & NL

Data Model Patterns A Metadata Map Book Review:

Data Model Patterns: A Metadata Map not only presents a conceptual model of a metadata repository but also demonstrates a true enterprise data model of the information technology industry itself. It provides a step-by-step description of the model and is organized so that different readers can benefit from different parts. It offers a view of the world being addressed by all the techniques, methods, and tools of the information processing industry (for example, object-oriented design, CASE, business process re-engineering, etc.) and presents several concepts that need to be addressed by such tools. This book is pertinent, with companies and government agencies realizing that the data they use represent a significant corporate resource recognize the need to integrate data that has traditionally only been available from disparate sources. An important component of this integration is management of the "metadata" that describe, catalogue, and provide access to the various forms of underlying business data. The "metadata repository" is essential to keep track of the various physical components of these systems and their semantics. The book is ideal for data management professionals, data modeling and design professionals, and data warehouse and database repository designers. A comprehensive work based on the Zachman Framework for information architecture—encompassing the Business Owner's, Architect's, and Designer's views, for all columns (data, activities, locations, people, timing, and motivation) Provides a step-by-step description of model and is organized so that different readers can benefit from different parts Provides a view of the world being addressed by all the techniques, methods and tools of the information processing industry (for example, object-oriented design, CASE, business process re-engineering, etc.) Presents many concepts that are not currently being addressed by such tools — and should be