Data Modeler's Workbench:
Tools and Techniques for Analysis and Design
by Steve Hoberman
A data model is the heart and soul of any application, providing a foundation
for efficient data entry and retrieval. It needs to be consistent with
other models within your organization, accurately capture the current
business requirements, and evolve to support changing business needs.
Data Modeler’s Workbench contains more than twenty finely tuned
tools aimed at improving the speed, accuracy, flexibility, and consistency
of your database, data warehouse, and operational applications. Steve
Hoberman explains each tool with the help of detailed examples, showing
how to apply each tool and where in the operational and reporting environment
each tool is most effective. You can customize the tools in this book
for your particular industry, organization, or project.
The companion Web site features:
Downloadable copies of the worksheets and checklists that modelers can
use on their own projects
Updates on the latest tools, techniques, and discussion forums
Links to other data modeling sites
The Data Modeling Handbook:
A Best-Practice Approach to Building Quality Data Models
by Michael C. Reingruber and William W. Gregory
A
Straightforward, No-Nonsense Guide to Building the Most Accurate, Complete,
and Useful Data Models Possible. How do I know if my data model is accurate?
When is a model really complete? Is it possible for a model to be both
technically perfect and of no use to an organization, and what can I
do to avoid that problem? This book provides answers to these and other
crucial data modeling questions. While there are plenty of books that
describe the characteristics of finished high-quality data models, only
The Data Modeling Handbook gets down to the nitty-gritty of actually
building one. Packed with real-world examples, annotated diagrams, and
a wealth of rules and best practices, this field-tested guide provides
experienced data modelers, architects, and engineers with hands-on guidance
from two noted data management experts.
The only book offering clear, straightforward rules and guidelines for
judging model accuracy and completeness
Presents all rules in several notations, including IDEF1X, Martin, Chen,
and Finkelstein
Compares
and contrasts the most popular modeling styles and demonstrates how
great models can be built using any
type of notation
Explains how to use an organization’s plans, policies, objectives,
and strategies to build accurate, complete, and useful models
Offers detailed guidance to establishing a continuous quality evaluation
program that’s easy to implement and follow
Packed with real-world examples and annotated diagrams illustrating
each point covered
Describes how to use Case tools most effectively to build high-quality
models
Information Modeling and Relational Databases:
From Conceptual Analysis to Logical Design
by Terry Halpin
Information Modeling and Relational Databases provides an introduction
to ORM (Object Role Modeling)-and much more. In fact, it's the only
book to go beyond introductory coverage and provide all of the in-depth
instruction you need to transform knowledge from domain experts into
a sound database design.
Inside, ORM authority Terry Halpin blends conceptual information with
practical instruction that will let you begin using ORM effectively
as soon as possible. Supported by examples, exercises, and useful background
information, his step-by-step approach teaches you to develop a natural-language-based
ORM model and then, where needed, abstract ER and UML models from it.
This book will quickly make you proficient in the modeling technique
that is proving vital to the development of accurate and efficient databases
that best meet real business objectives.
The most in-depth coverage of Object Role Modeling available anywhere-written
by a pioneer in the development of ORM.
Provides additional coverage of Entity Relationship (ER) modeling and
the Unified Modeling Language-all from an ORM perspective.
Intended for anyone with a stake in the accuracy and efficacy of databases:
systems analysts, information modelers, database designers and administrators,
instructors, managers, and programmers.
Explains and illustrates required concepts from mathematics and set
theory.
Via a companion Web site, provides answers to exercises, appendices
covering the history of computer generations, subtype matrices, and
advanced SQL queries, and links to downloadable ORM tools.
Business
Rules Applied: Building Better Systems Using The Business Rules Approach
by Barbara von Halle
Representing
a significant change of focus in software engineering, the business
rule approach to application development benefits all decision makers.
Managers looking to take advantage of new opportunities will turn to
business rules to implement change. IT has already learned the benefits
of separating data by processing and managing data as an independent
component of systems. A rules-extended development approach does exactly
the same thing for business rules: by reducing the amount of code that
needs to be written, it shortens the time necessary to implement change.
Bestselling author Barbara von Halle (The Handbook of Relational Database
Design from Addison Wesley) presents the first book to show in practical,
real-world terms how to build applications using business rule concepts
and techniques.
This authoritative guide will give readers:
• Complete guidance for system designers and database managers
• The motivation for using the business rule approach
• Techniques for discovering and managing rules
• Guidance on how to conduct rule analysis
• Steps for designing the implementation options of the rules,
as well as designing workflow and database components
Entity-Relationship
Modeling: Foundations of Database Technology
by Bernhard Thalheim
Database technology and entity-relationship (ER) modeling have meanwhile
reached the level of an established technology. This book presents the
achievements of research in this field in a comprehensive survey. It
deals with the entity-relationship model and its extensions with regard
to an integrated development and modeling of database applications and,
consequently, the specification of structures, behavior and interaction.
Apart from research on the ER model and the syntax, semantics, and pragmatics
of database modeling the book also presents techniques for the translation
of the ER model into classical database models and languages such as
relational, hierarchical, and network models and languages, and also
into object-oriented models. The book is of interest for all database
theoreticians as well as practitioners who are provided with the relevant
foundations of database modeling.
Data Modeling is about gathering, documenting, and communicating the
elements and structure of business information. What begins as a conceptual
interplay of logical data units, through the application of relational
theory, becomes the basis for creating a physical database design.
Data Modeling is a core skill for data professionals, and is a full
time job for a small but growing number of IT practitioners. It is
a crucial stage prior to good quality relational database design.
Data Modeling for Everyone is for those who:
Have no previous data modeling experience
Want to understand the role of the data modeler in database design
Need to know how to capture the essence of a system but don't know
where to start
Want more than just the theory and learn best from real world experience
Require a book before other data design books – helping you
develop a logical model rather than assuming one exists that needs
to be implemented in a database
Data Modeling for Everyone provides a solid foundation in the following
tools & techniques:
The different types of data modeling – enterprise, transactional,
and dimensional
The stages of analysis – developing conceptual, logical, and
physical models
What to do if you need to work with existing systems – reverse
engineering and forensic analysis
General principles for converting logical models to physical ones
Modeling scope – focusing on what's important but allowing for
future development of your model
Defining detail – entity relationship (E/R), key based, and
fully attributed models
Documenting your understanding of the business in the model
Graphical data modeling, focusing on the IDEF1X notation
