"The Data Model Resource Book, Revised Edition, Volume 1 is the best book I?ve seen on data architecture. It does not merely address the top levels of a data architecture (Zachman Framework row one or two); it provides both common and industry-specific logical models as well as data designs that may be customized to meet your requirements. The end result is a is a rich framework whose models span the higher and lower levels of a data architecture, including high-level models, logical models, warehouse designs, star schemas, and SQL scripts. You can use the data models, designs, and scripts as templates or starting points for your own modeling, an introduction to subject areas you might not be familiar with, a reference to validate your existing models, and a help to building an enterprise data architecture. The book provides techniques to transform models from one level to another, as well as tips and techniques for getting the appropriate levels of abstraction in the models. Instance tables (sample data) help bring the models to life. I have customized and used the models from the first edition on many projects in the last two years?it is an invaluable resource to me."
--Van Scott, President, Sonata Consulting, Inc.

"Len Silverston has produced an enormously useful two-volume compendium of generic (but not too generic) data models for an extensive set of typical enterprise subject areas, and for various industries that any data modeler will likely encounter at some point in his or her career. The material is clearly written, well organized, and goes below the obvious to some of the more perverse and difficult information requirements in an enterprise. This is an invaluable resource for doing one's homework before diving into any modeling session; if you can't find it here, there is certainly a very similar template that you can use for just about any situation with which you might be faced."
--William G. Smith, President, William G. Smith & Associates

"In today's fast-paced e-oriented world, it is no longer acceptable to bury business constraints in hard-to-change data structures. Data architects must comprehend complex requirements and recast them into data architecture with vision for unforeseen futures. Len's models provide an outstanding starting point for novice and advanced data architects for delivering flexible data models. These models position an organization for the business rule age. Their proper implementation and customization allows the organization to externalize and manage business policies and rules so that the business can proactively change itself. In this way, the data architecture, based on Len's models and procedures for customizing them, becomes by design the foundation for business change."
--Barbara von Halle, Founder, Knowledge Partners, Inc., Co-author of Handbook of Relational Database Design

"These books are long overdue and a must for any company implementing universal data models. They contain practical insights and templates for implementing universal data models and can help all enterprises regardless of their level of experience. Most books address the needs for data models but give little in the way of practical advice. These books fill in that void and should be utilized by all enterprises."
--Ron Powell, Publisher, DM Review

"Businesses across the world are demanding quality systems that are built faster by IT shops. This book provides a foundation of patterns for data modelers to expand upon and can cut days, if not weeks, off a project schedule. I have found The Data Model Resource Book, Revised Edition, Volume 1 valuable as a resource for my modeling efforts at L.L. Bean, Inc. and feel it is an essential component in any modelers toolkit."
--Susan T. Oliver, Enterprise Data Architect, L.L. Bean, Inc.

"I was first introduced to The Data Model Resource Book three years ago when I was hired by a firm who wanted an enterprise data model. This company did not believe the dictum that ?all companies are basically the same;? they felt they were somehow unique. After a little analysis with Len Silverston's help, we found that we were actually quite a bit the same: we had customers, accounts, employees, benefits, and all the things you'd find in any corporation. All we had to do was adapt the product component of Len's book and we were ready to move ahead with a great framework for all of our data. A CD-ROM that accompanies the book provided scripts to build the model in Oracle very quickly. We then began mapping all of our detailed data types to the enterprise model and, voila, we could find a place for all of those various spellings and misspellings of Account Number.
Volume 2 of this revised edition provided even more exciting features: models of industry-specific data. I began to see interesting patterns that permeated this volume. For example, a reservation is a reservation, whether you're an airline, a restaurant, or a hotel. (We even have something similar in the oil industry--the allocation.)
Another concept from the book that has changed my thinking and vocabulary is the word "party." I recently managed a project in which an employee could also function as a customer and as an on-line computer user. The team was in disagreement regarding a name for this entity; but after checking The Data Model Resource Book, we realized that here we had a party playing three roles.
Whether your job is to jump-start a data warehouse project or borrow ideas for any subject area in your next operational database, I highly recommend The Data Model Resource Books, Revised Edition, Volumes 1 and 2 as your bible for design."
--Ted Kowalski, Equilon Enterprises LLC, Author of Opening Doors: A Facilitator's Handbook

"Len Silverston has produced an enormously useful two-volume compendium of generic (but not too generic) data models for an extensive set of typical enterprise subject areas, and for various industries that any data modeler will likely encounter at some point in his or her career. The material is clearly written, well organized, and goes below the obvious to some of the more perverse and difficult information requirements in an enterprise. This is an invaluable resource for doing one's homework before diving into any modeling session; if you can't find it here, there is certainly a very similar template that you can use for just about any situation with which you might be faced."-- William G. Smith President, William G. Smith & Associates

"In today's fast-paced e-oriented world, it is no longer acceptable to bury business constraints in hard-to-change data structures. Data architects must comprehend complex requirements and recast them into data architecture with vision for unforeseen futures. Len?s models provide an outstanding starting point for novice and advanced data architects for delivering flexible data models. These models position an organization for the business rule age. Their proper implementation and customization allows the organization to externalize and manage business policies and rules so that the business can proactively change itself. In this way, the data architecture, based on Len's models and procedures for customizing them, becomes by design the foundation for business change."--Barbara von Halle Founder, Knowledge Partners, Inc. Co-author of Handbook of Relational Database Design

"These books are long overdue and a must for any company implementing universal data models. They contain practical insights and templates for implementing universal data models and can help all enterprises regardless of their level of experience. Most books address the needs for data models but give little in the way of practical advice. These books fill in that void and should be utilized by all enterprises."--Ron Powell Publisher, DM Review

"I was first introduced to The Data Model Resource Book three years ago when I was hired by a firm that wanted an enterprise data model. This company did not believe the dictum that "all companies are basically the same;" they felt they were somehow unique. After a little analysis with Len Silverston's help, we found that we were actually quite a bit the same: we had customers, accounts, employees, benefits, and all the things you'd find in any corporation. All we had to do was adapt the product component of Len's book and we were ready to move ahead with a great framework for all of our data. A CD-ROM that accompanies the book provided scripts to build the model in Oracle very quickly. We then began mapping all of our detailed data types to the enterprise model and, voila, we could find a place for all of those various spellings and misspellings of Account Number.

Volume 2 of this revised edition provided even more exciting features: models of industry-specific data. I began to see interesting patterns that permeated this volume. For example, a reservation is a reservation, whether you're an airline, a restaurant, or a hotel. (We even have something similar in the oil industry--the allocation.)

Another concept from the book that has changed my thinking and vocabulary is the word "party." I recently managed a project in which an employee could also function as a customer and as an on-line computer user. The team was in disagreement regarding a name for this entity; but after checking The Data Model Resource Book, we realized that here we had a party playing three roles.

Whether your job is to jump-start a data warehouse project or borrow ideas for any subject area in your next operational database, I highly recommend The Data Model Resource Books, Revised Edition, Volumes 1 and 2 as your bible for design."--Ted Kowalski Data Architect, Equilon Enterprises LLC Author of Opening Doors: A Facilitator's Handbook

• Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than 150,000 copies
• Delivers real-world solutions for the most time- and labor-intensive portion of data warehousing-data staging, or the extract, transform, load (ETL) process
• Delineates best practices for extracting data from scattered sources, removing redundant and inaccurate data, transforming the remaining data into correctly formatted data structures, and then loading the end product into the data warehouse
• Offers proven time-saving ETL techniques, comprehensive guidance on building dimensional structures, and crucial advice on ensuring data quality

The extract, transform, and load (ETL) phase of the data warehouse development life cycle is far and away the most difficult, time-consuming, and labor-intensive phase of building a data warehouse. Done right, companies can maximize their use of data storage; if not, they can end up wasting millions of dollars storing obsolete and rarely used data. Bestselling author Ralph Kimball, along with Joe Caserta, shows you how a properly designed ETL system extracts the data from the source systems, enforces data quality and consistency standards, conforms the data so that separate sources can be used together, and finally delivers the data in a presentation-ready format.

Serving as a road map for planning, designing, building, and running the back-room of a data warehouse, this book provides complete coverage of proven, timesaving ETL techniques. Beginning with a quick overview of ETL fundamentals, it then looks at ETL data structures, both relational and dimensional. The authors show how to build useful dimensional structures, providing practical examples of techniques.

Along the way you’ll learn how to:

• Plan and design your ETL system
• Choose the appropriate architecture from the many possible options
• Build the development/test/production suite of ETL processes
• Build a comprehensive data cleaning subsystem
• Tune the overall ETL process for optimum performance

Building a data warehousing and business intelligence system is a complex business and engineering effort. While there are significant technical challenges to overcome in successfully deploying a data warehouse, the authors find that the most common reason for data warehouse project failure is insufficient focus on the business users and business problems. In an effort to help people gain success, this book takes the proven business Dimensional Lifecycle approach first described in best selling The Data Warehouse Lifecycle Toolkit and applies it to the microsoft SQL Server 2005 tool set.

Beginning with a thorough description of how to gather business requirements, the book then works through the details of creating the target dimensional model, setting up the data warehouse infrastructure, creating the relational atomic database, creating the analysis services databases, designing and building the standard report set, implementing security, dealing with metadata, managing ongoing maintenance and growing the DW/BI system. All of these steps tie back to the business requirements. Each chapter describes the practical steps in the context of the SQL Server 2005 platform.

Intended Audience

The target audience for this book is the IT department or service provider (consultant) who is:

• Planning a small to mid-range data warehouse project;
• Evaluating or planning to use microsoft technologies as the primary or exclusive data warehouse server technology;
• Familiar with the general concepts of data warehousing and business intelligence.

The book will be directed primarily at the project leader and the warehouse developers, although everyone involved with a data warehouse project will find the book useful. Some of the book’s content will be more technical than the typical project leader will need; other chapters and sections will focus on business issues that are interesting to a database administrator or programmer as guiding information.

The book is focused on the mass market, where the volume of data in a single application or data mart is less than 500 GB of raw data. While the book does discuss issues around handling larger warehouses in the microsoft environment, it is not exclusively, or even primarily, concerned with the unusual challenges of extremely large datasets.

About the Authors

JOY MUNDY has focused on data warehousing and business intelligence since the early 1990s, specializing in business requirements analysis, dimensional modeling, and business intelligence systems architecture. Joy co-founded InfoDynamics LLC, a data warehouse consulting firm, then joined microsoft WebTV to develop closed-loop analytic applications and a packaged data warehouse.

Before returning to consulting with the Kimball Group in 2004, Joy worked in microsoft SQL Server product development, managing a team that developed the best practices for building business intelligence systems on the microsoft platform. Joy began her career as a business analyst in banking and finance. She graduated from Tufts University with a BA in Economics, and from Stanford with an MS in engineering Economic Systems.

WARREN THORNTHWAITE has been building data warehousing and business intelligence systems since 1980. Warren worked at Metaphor for eight years, where he managed the consulting organization and implemented many major data warehouse systems. After Metaphor, Warren managed the enterprise-wide data warehouse development at Stanford University. He then co-founded InfoDynamics LLC, a data warehouse consulting firm, with his co-author, Joy Mundy. Warren joined up with WebTV to help build a world class, multi-terabyte customer focused data warehouse before returning to consulting with the Kimball Group. In addition to designing data warehouses for a range of industries, Warren speaks at major industry conferences and for leading vendors, and is a long-time instructor for Kimball University. Warren holds an MBA in Decision Sciences from the University of Pennsylvania's Wharton School, and a BA in Communications Studies from the University of Michigan.

RALPH KIMBALL, PH.D., has been a leading visionary in the data warehouse industry since 1982 and is one of today's most internationally well-known authors, speakers, consultants, and teachers on data warehousing. He writes the "Data Warehouse Architect" column for Intelligent Enterprise (formerly DBMS) magazine.

Back Cover Copy

As longtime data warehousing practitioners and former microsoft insiders, authors Joy Mundy and Warren Thornthwaite have extensive experience in building and managing data warehouse (DW) and business intelligence (BI) systems. With this book, they share best practices for using SQL Server 2005 to build a successful DW/BI system. Covering the complete suite of data warehousing tools that accompanies SQL Server 2005, they focus on the full project lifecycle, including design, development, deployment, and maintenance.

You'll learn how and when to use BI tools such as Analysis Services, Integration Services, and the SQL Server database to accomplish various data warehousing tasks. A helpful case study used throughout the book provides examples of the techniques presented. You'll find practical guidance for every member of the data warehouse team and learn how to:

• Identify high-value business requirements and build organizational support for the project
• Design an information infrastructure for the enterprise using established dimensional design
• Design and build a flexible and powerful ETL system to clean, align, and restructure data for business use
• Provide decision makers with tools to analyze business problems and opportunities
• Use data mining to uncover data relationships and trends
• Build BI applications in Reporting Services
• Maintain, secure, and operate the DW/BI system

Visit the companion Web site at www.wiley.com/go/MsftDWToolkit

The companion Web site contains all the code samples, the sample database used throughout, sample templates, and other job aids.

Whether you're a systems administrator, database application developer, or IT consultant, you'll quickly ratchet up your knowledge of microsoft SQL Server 2005 with this thorough and comprehensive guide. Light on theory and heavy on practicality, it cuts to the chase with real-world examples of large-scale business applications, an entire chapter on troubleshooting, and crucial information on SQL Server 2005's enhanced connectivity. For new users of microsoft SQL Server, this book takes you quickly, but systematically, through the introductory topics.

Coverage Includes

• Integrating SQL Server with .NET Framework
• Understanding Service Broker, a distributed application framework
• Programming with ADO.NET, the data-access component of .NET
• Setting up Notification Services, which delivers personalized information to mobile devices
• Using SQL Server management Studio instead of Enterprise Manager
• Designing made easier with new business Intelligence Development Studio (BIDS)
• Printing multi-page reports
• Mastering Transact-SQL programming language

Leverage the Experience of Large-Scale Enterprises through Real-World Examples

Increase Your Own Productivity with an Entire Chapter on Troubleshooting

Discover What SQL Server 2005's Increased Emphasis on Connectivity Means to Your Installation

Start Developing Apps—All the Information You Need!

www.sybex.com

The book's commonsense approach provides exemplary project management skills tailored to gathering (and refining, implementing, and eventually tracking) software requirements. While the book often cites recent software engineering studies, the focus always returns to practical management techniques. A case study for a chemical tracking application frames the book, and most chapters begin with anecdotes that demonstrate situations in which users and developers misunderstand each other about a software project's ultimate goals. (If you've ever worked in the field, these stories will probably sound all too familiar.)

This book offers hope, though, for improving your software design process, with dozens of tips on getting better design input from your customers and then using these requirements to generate a variety of design documents. There are numerous templates and sample documents too--a big help for the busy software manager.

Several standout sections cover negotiating difficult steps in the process, particularly how to manage shifting requirements as projects move forward and keep the various users and stakeholders content throughout the software process. Late in the book, the author surveys today's software management tools and shows how to pick the right ones for your organization.

Anchored by the author's considerable experience and software engineering expertise, this jargon-free and practical guide to software requirements can definitely give you the edge in managing software projects more efficiently. --Richard Dragan

Topics covered: software requirements specifications (SRS); business and user requirements; risk management; the requirements process; sample documents and templates; requirements development: elicitation, analysis, specification, and verification; rights and responsibilities for software customers; best practices; project management tips; process assessment and improvement; types of users; product champions; use cases and other diagrams; tips for prototyping; managing requirements change; change centered boards (CCBs); evaluating and using requirements tools; requirements traceability matrix; impact analysis. --This text refers to an out of print or unavailable edition of this title.

Book Description
Learn proven, real-world techniques for managing the software requirements engineering process. Includes use cases, up-to-date tools, more field examples, and a new troubleshooting guide. Softcover.