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Analytical Modeling Manifesto

Tom Haughey
President
InfoModel

This presentation will re-examine the concept of data design for analytical systems such as the data warehouse. It will take a close look at dimensional modeling and define its proper role and context. It will position ER modeling, dimensional modeling (and other forms) into a general framework. Dimensional modeling is usually presented as the end-all and be-all of data warehousing. Is dimensional modeling one of the great con jobs in data management history? In fact, dimensional modeling has strengths and weaknesses. In some ways it has become outmoded. In other ways, it has been around for decades (and will continue to be). There are three ways to improve performance: use better hardware, use better software and optimize the data. The primary justification for dimensional modeling is to improve performance by compromising the data to compensate for the inefficiency of technology. It uses the third method above. A secondary purpose is to provide a consistent base for analysis. Dimensional modeling comes with a price and with restrictions. There are times and places where dimensional modeling is appropriate and will work, and other times and places where it is inappropriate and will actually interfere with the goals of a warehouse.

To make matters worse, the data warehouse industry suffers from a host of double-entendres that make it difficult to communicate meaningfully. It is not uncommon for two “gurus” to disagree about something without realizing that they are not talking about the same thing. Because of this it is actually necessary to start over and define some terms. This presentation will do just that: it will reexamine these concepts and redefine them; it will establish a framework for integration; and it will address a number of specific analytical modeling issues or situations, such as the following:

- The main characteristics of analytical models
- How to distinguish logical from physical models
- The importance of using principles (not patterns) to do design
- How to do database optimization
- Logical vs physical models
- ER model vs. dimensional model
- Data model optimization
- Different fundamental grains of facts
- Seamless extensibility of a database
- Changing dimensions
- Assignment of keys, including surrogate keys aggregates
- Prodigal data
- Ragged hierarchies
- Dimensions with multiple values or roles
- Representing what did and did not happen
- Conforming dimensions
- Unexpected data
- Time variant models
- Dealing with changes in the model

Tom Haughey is one of four originators of Information Engineering in America. He was most recently CTO for Pepsi Bottling Group after being Pepsico’s Director of Enterprise Data Warehousing. His courses have been delivered to companies around the world. He has worked on the development of seven different CASE and wrote his own in 1984. He formerly worked for IBM for 17 years. He is the author of many articles on DW and IE. He was VP of Technology for Silverrun Technologies. He is working on a book, "Designing the Data Warehouse - The Real Deal". Tom earned a BA in English.

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Information Quality in an Integrated ERP Production Environment

Danette McGilvray
Enterprise Information Quality Program Manager
Agilent Technologies

You have now completed the migration from legacy systems to your new transactional environment – an ERP (Enterprise Resource Planning) application. Let’s assume the data was cleaned, transformed and migrated according to business requirements, the users received training on how to use the new system, and your new processes are all in place. Congratulations! Now what?

After your well-deserved vacation ask “Are my information quality concerns over?” Unfortunately, the answer is “NO!” Without on-going management of your company’s production data the quality immediately starts degrading. New challenges for information quality and data management arise in an integrated environment that did not previously exist in the separate legacy systems. While an integrated ERP system can help with the consistency of data, it cannot ensure accuracy and you cannot depend on front-end edits to maintain your information quality. An emphasis on quality is needed due to the high risk of endangering the integrity of the production environment – changes in one area quickly impact other areas. Learn how one global Fortune 500 company is handling these challenges.

Danette McGilvray: As the enterprise information quality program manager, Ms. McGilvray leads a program that helps Agilent institute best practices for managing information quality on an enterprise-wide basis. She has been involved with a large-scale data migration project at Agilent and is now focusing efforts on information quality in the ERP production environment. She consults with and leads project teams and speaks frequently at industry conferences. She was featured in a PC Week article about data quality and some of her program's best practices are highlighted in Larry English's book “Improving Data Warehouse and Business Information Quality. Her experience includes information resource management, direct marketing, and electronic data interchange.

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Developing a Business Rules Strategy using a Business Rules Special Interest Group Approach

Tom Yanchek
Project Manager - Infrastructure
UPS

As more and more business rule enthusiasts and practitioners attempt to introduce a business rule approach/strategy within their organization, there is often an immediate reaction to ‘nip this thing in the bud.’ By establishing a business rule committee or Special Interest Group approach, management may then realize the importance of:

When organizations start to build new enterprise wide applications, or are integrating legacy systems the same question arises; ‘What are the business rules for this initiative?’ or ‘does anyone know where we can get all the rules for our shipping procedures?’ Unfortunately, these questions being raised are usually coming from the business users who should have supplied that information or have business rules and want to see them put in place and enforced.

The lack of an organized strategy and approach that accurately and clearly presents the benefits of a business rule management could result in the organization setting itself up for inaccurate business rule definitions which Inevitably will result in embarrassing failures during new product launches or system integration and implementation. Understanding what to present and how to present a business rule strategy can result in much needed cooperation and welcome successes once implemented.

Tom Yanchek is a Manager at United Parcel Services in Morristown, New Jersey. Tom is actively involved in developing business requirements and enterprise architecture solutions for UPS’ package billing applications. An integral part of his role at UPS included the development of a business rule capture procedure and he has recently defined a business rule management approach. Tom has over 30 years of application development and enterprise architecture development experience and his exposure to business rule management started in 1989. In addition to his development experience, Tom has managed numerous enterprise architecture development projects within the Pharmaceutical, Retail, Telecommunications and Insurance industries. He has also taught data modeling, relational database design and has spoken at various seminars/conferences and written articles on business rule capturing techniques and business rule management approaches.

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Web based Dynamic Data Dictionary

Lee Arnett
Data Warehouse Architect
Quantum, Inc.

There is an old adage “You can lead a horse to water, but you can’t make him drink”. This applies to data warehouse reporting as well. You can develop a data warehouse and provide access, but how do you get people to report from it? One way is to provide an easy to use, accurate, data dictionary to assist people in getting correct information from the warehouse. We accomplished this by creating a web based data dictionary sourced from our meta data. The construction and deployment of a web based dynamic data dictionary I sused as a case history.

Lee Arnett is currently employed at Quantum, Inc. in the position of Data Warehouse Architect. He has been working in the area of Data Warehouse since 1996. Since that time he has been designing and building data warehouses and OLAP data marts for internal use and commercial products. Much of this time was spent doing dimensional modeling and multidimensional data base development. After starting his IT career at IBM in 1978, Mr. Arnett has worked for several world-class organizations including ChannelPoint, Focus on The Family, and Kaiser Foundation Health Plan.

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FGDC MetaData and Oracle Spatial Data Integration

Mike Walls Executive Consultant Plangraphics, Inc.

This is a presentation of a database schema that encompasses the entire FGDC Spatial Data Metadata Standard, with JSP that manages a web user interface. Java provides a means to automatically catalogue spatial data stored in Oracle Spatial sdo_geometry format. A set of java classes manages the interface and schema. This topic will introduce a means for documenting geospatial data already stored in a database, using the FGDC Metadata Standard.

Paul has 10 years in the field of GIS programming and data management, with 15 years in RDBMS management. He has worked in the fields of GIS for environmental needs assessment (ESRI) and telecommunications (Iridium) with special focus on spatial data management in Oracle.

Mike Walls is Software Engineering Manager for PlanGraphics, Inc., a world leading consulting firm specializing in GIS and its integration into enterprise information technology and management. He specializes in project management and data architecture issues, but still works on complex data modeling and database design challenges as needed. Prior to joining PlanGraphics, he worked for over 20 years in local government as a policy analyst, city planner, applications programmer and systems administrator. Mr. Walls has academic degrees in anthropology, public administration, and computer science. He has also recently completed 28 hours towards a doctorate in geography. He has over 17 years of hands-on experience designing and implementing GIS. In 1999, URISA published his “Data Modeling” in their Quick Start monograph series.

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PANEL: Data Challenges in Getting to the Single Customer View

Ulka Rodgers President eTransitions, Inc.

Denise Hopkins Director of Strategic Marketing Experian

Rich Olshefski Principal Consultant Innovative Systems, Inc.

Every sales group asks for the "full view" of customers – a substantial task, invariably requiring the integration of multiple customer touch points (and therefore, data sources). So, what are the implications for data managers, and what toolbox can you draw from in order to satisfy the demands of the business?

This unique session will draw on the expertise of individuals who have faced just about every CRM scenario you can imagine. Responding to the specific questions below, we'll ask them to explain how each one would approach the problems and issues involved.

Ulka Rodgers is a well-known speaker and author of three books about database management systems. She is the founder of eTransitions, Inc and is based in New Jersey. Ulka has over 22 years of experience in modeling from individual application models to enterprise-level models. Her special expertise is involvement in the lifecycle from IT strategy planning through implementation and transition to new applications.

Denise Hopkins is responsible for marketing strategy for Experian’s Database Solutions business unit. Denise’s responsibilities include market planning and strategy development for Database Solutions’ data integration service, Truvue, as well as its Hosted database services. Denise is a highly regarded within the CRM industry for her data integration and data quality expertise, and has spoken at many trade shows and conferences, including NCR Partners and Gartner CRM Summit. Denise has over 10 years of experience in database marketing and financial services marketing.

Rich Olshefski is a Principal Consultant with Innovative Systems, Inc., headquartered in Pittsburgh, PA. Innovative Systems has been successful in delivering customer data integration solutions to organizations worldwide, whose success depends on a complete and accurate understanding of their customers. Mr. Olshefski, with over 20 years in the Information Quality field, has been instrumental in several facets of the customer data integration evolution, including the development of international data quality knowledge-bases; design of the world’s only customer data quality auditing software; and compilation of a one-of-a-kind data quality benchmarking database. Mr. Olskefski has been with Innovative Systems since 1981. His experience has provided him with the skills necessary to guide organizations to establish high quality customer repositories, and to put processes and procedures in place to maintain and enhance that quality as needs change. Mr. Olshefski holds a Master of Science degree in Information Science from the University of Pittsburgh.

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Got Any Change to Spare? A Practical, Working Approach to Database Change Control

Stephen Ward
Data Architect
Sprint Corp.

Database change control is the process of managing the changes that occur during the life of a database system, from initial request through implementation. This session will first review several alternative approaches to database change control, weighing the benefits, issues and risks associated with each. Next a case study on an in-house developed Database Change Control System at Sprint will be presented. The Database Change Control System consists of a defined process for change control, automated by a web application that provides a robust set of functionality including Submit Request, Track Request, Approve Request, and Fulfill Request. Finally, several cultural aspects of deploying a system for database change control will be discussed.

The attendee will learn:

Stephen Ward has 20 years of experience in the data processing industry, working for firms in the defense, manufacturing, engineering and telecommunications sectors. Mr. Ward has developed systems on many heterogeneous platforms, serving in a variety of roles including Project Manager, Architect, Process Analyst, Data Analyst, Programmer, Database Administrator and System Administrator. Currently Mr. Ward is a Lead Data Architect at Sprint Corporation, designing operational and DSS databases on the Oracle and Teradata DBMS systems for telecommunications applications. He has also lead/contributed on numerous standards and process teams, including Data Modeling Standards, Oracle DBA Standards and Database Development Methodology.

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Data Modeling for Authentication and Entitlement

William Lewis
Senior Technology Specialist
Cambridge Technology Partners

In the current environment of political upheaval, corporate downsizing and consolidation, and extended value chains, security-related applications including identity authentication and entitlement have become increasingly critical. Up to this point, requirements analysis for authentication and authorization have typically been driven from a technology and product-driven viewpoint.

This presentation will describe an alternative, data-driven approach for analyzing and modeling the communities, resources and rules required to enable appropriate and secure acces to corporate digital assets. This approach will be compared with current implementation approaches including single signon, LDAP directories and portals.

Attendees will learn:

Bill Lewis's extensive experience in information technology covers many areas of data management, including data modeling, database design, metadata management, data security and data warehousing. In the past two years, his focus has expanded to include the delivery of integrated, rules-based knowledge management, identity management and portal solutions to clients in manufacturing and financial services. His book Data Warehousing and E-Commerce (Prentice Hall PTR, 2001) includes coverage of current topics in business rules and identity management.

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Data Quality @ Bulgari: a real case study.

Alberto Villari
Data Quality Manager
Bulgari S.p.A.

This presentation conveys the true experience of a 3-year data quality project. Bvlgari produces and sells 50.000 different products. There was an urgent need to qualify those products to enable marketing and top management to analyze the performance of different product lines, designs, materials etc. From the moment that the company decided to enrich the information about products, we decided to start a corporate project to assess how should this information be made available. In particular we assessed Data Ownership, Data Usership and implementation responsibility.

Between data Owners and Users the qualification of new information was shared and agreed. Data Owners signed a "contract" in which they took the responsibility of providing the right information at the right time in the right place. Data Implementers were committed to feeding well-defined product master tables as provided by data owners.

The main project phases were:

Alberto Villari: IT Graduate on 1993; Consultant as OO Developer, then Database analyst for 5 years. In Bulgari from 1998 as DWH manager, running the Bulgari Data Quality project from 2000, and Data Quality manager from 2002.

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Business Rules and Rule Engines: Opening New Doors of Opportunity

Ronald Ross
Principal
Business Rule Solutions, LLC

What are business rules, and how can you apply them effectively in your organization? This presentation brings you up-to-date on the concepts, techniques and tools of the business rule approach, and discusses what you need to know to be successful with them in your organization. Eight Principles of the Business Rule Approach will be examined, and guidance will be offered about how to apply each one successfully.

In addressing these Principles, key techniques of business rule methodology will be discussed, including Policy Charters, Fact Models, and Rule Books. The role of workflow models and procedures will be examined, as will the need for rule repositories and rule management.

Finally, this workshop reviews business rule engines – how they work and how they can be classified based on architecture and problem orientation. In all, this workshop will give you the very latest on exactly what the Business Rule Approach means in practice.

Ronald G. Ross is Co-Founder and Principal of Business Rule Solutions, LLC (www.BRSolutions.com). BRS provides workshops, consulting services, publications, and methodology supporting business analysis, business rules, and rule management. At BRS, Mr. Ross co-develops Proteus™, its landmark business analysis methodology, which features numerous innovative business rule techniques including the popular RuleSpeak™ (available free through www.BRCommunity.com). These are the latest offerings in a 25-year career that has consistently featured creative, business-driven solutions. Mr. Ross also serves as Executive Editor of www.BRCommunity.com and its flagship on-line publication, Business Rules Journal. He is a regular columnist for the Journal’s Commentary section which also features John Zachman, Chris Date and Terry Halpin. BRCommunity.com, hosted and sponsored by BRS, is a vertical community for professionals working with business rules and related areas. Mr. Ross was formerly Editor of the Data Base Newsletter from 1977 to 1998. Mr. Ross is recognized as the “father of business rules.” He serves as Co-Chair of the Business Rule Forum Conference. He was a charter member of the Business Rules Group in the 1980s, and was a co-editor of its watershed 2000 paper, “Organizing Business Plans: The Standard Model for Business Rule Motivation.” He has received several industry awards, including DAMA International’s Individual Achievement Award for 1995. Mr. Ross is the author of a half-dozen professional books. His newest work, Principles of Business Rule Systems, is scheduled for release by Addison-Wesley in 1Q 2003. Other recent books on business rules include Business Rule Concepts (1998) which provides an easy-to-read, non-technical explanation of business rules, and The Business Rule Book (Second Edition, 1997) which presents a new and revolutionary approach to categorizing and modeling business rules in declarative form. Mr. Ross received his M.S. in information science from Illinois Institute of Technology, and his B.A. from Rice University.

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Understanding and Leveraging the Object Management Group’s Metadata Standards

Charles Betz
Metadata Management Office
Best Buy

Over the past several years, the Object Management Group has organized a very substantial series of collaborative intellectual processes. These efforts have been aimed at defining a lingua franca for metadata and modeling language description, and have resulted in specifications such as the Unified Modeling Language, the Meta-Object Facility, XML Metadata Interchange, and the Common Warehouse Metamodel (as well as many others). This presentation will provide an accessible overview of these efforts and their industry relevance, from the perspective of an interested Fortune 100 data administrator. The concept of a MOF-based unified metadata bus architecture will also be briefly explored.

Charles Betz heads the Metadata Management Office for electronics retailer Best Buy. He previously spent 2 years at Target Corporation building that company’s metadata repository, work documented in Chapter 23 of Adrienne Tannenbaum’s recent Metadata Solutions. He is finishing his Master’s of Science in Software Engineering at the University of Minnesota this spring.

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PANEL: The Semantics of Semantics

Dave McComb (Moderator)
Semantic Arts

Donald Chapin Business Language & Rules Consultant Business Semantics Ltd.

Zvi Schreiber Founder Unicorn Solutions Inc.

Semantics can be broadly defined as the study of "meaning" in language. Yet as we hear the word used increasingly in IT circles -- in contexts such as the Semantic Web, semantic integration, semantic modeling, data semantics, etc. -- then it becomes more difficult to settle on a single definition of the word. What does semantics really mean in all these different contexts? And more interestingly still, why is semantics becoming more pervasive in data and IT conversations today?

The answer is that a great many business and IT initiatives are happening that are providing a need for businesses to come to grips with semantics. XML, and its technologically-related offspring -- the semantic web and web services -- are very significant. But so too are new requirements for rule expression, data sharing and knowledge portals. Projects that depend on content management and/or search technologies are also driving the need.

Formal semantics also improve data management. The number of data technologies (XML, RDBMS, legacy, etc.), data standards, and disparate data schemas in use in enterprises continues to proliferate. A deep understanding of the informational value of data assets and the relationship between them can support the entire lifecycle of a data asset, from conception to decommissioning, analyzing the impact of each change along the way. Formal semantics give a common understanding, and this understanding can automate intricate data translation work, a key component of data integration.

Donald Chapin has pioneered methods for defining data, structuring knowledge, and expressing business rules in the language of the business since the beginning of his career. Having co-founded a manufacturing company with responsibility for its organization, processes, management system and recordkeeping, he proceeded to bring that business orientation to the design of IBM's first training program for business application development. His work co-designing DBDA, IBM's first database design tool, started with business people naming the data on their forms and reports in their own business language, so the tool could bridge from the business to the database design. He helps clients to bridge work and systems with the language of their business as a tools and methods consultant, workshop facilitator, trainer, mentor, and quality monitor. Donald is a member of the Business Rules Group, and co-editor of its new "Organizing Business Concepts" standard under development.

Zvi Schreiber is Founder of Unicorn Solutions, a member of the W3C’s Semantic Web Activity and Web Ontology Working Group. Unicorn is also the Technical Coordinator of the European Union's Corporate Ontology Grid Project. Schreiber has been delivering new software architectures to the world's largest enterprises for over a decade. Prior to Unicorn, he founded Tradeum, Inc., pioneering B2B e-commerce in direct goods by way of matching flexible XML specifications of transactions. Schreiber holds a Ph.D. in Theoretical Computer Science from Imperial College of Science in London. He has lectured and published widely on subjects related to applying formal models to problems in enterprise IT.

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Managing the XML Data Resource

Richard Warner
Enterprise Data Architect
Engelhard Corporation

There’s more to Data Resource Management than relational and dimensional data. Managing the tagged data in XML documents is also crucial to managing the enterprise data resource. This will become increasingly true as your organizations embrace B2B and B2C opportunities.

Englehard Corporation, a F500 specialty chemicals company, is using XML to support a major ebusiness initiative. This presentation describes how the principles of Data Resource Management have been applied to the development of a robust, coherent strategy for managing XML and XML data resources, and how the lessons learned at Engelhard can be applied within your enterprises. Attendees will learn how they can leverage their skills as data resource professionals to support the effective use of XML within their enterprises.

Dr. Richard Warner is Enterprise Data Architect at Engelhard Corporation, a F500 specialty chemicals company. He joined Engelhard after 17 years as a consultant specializing in the analysis, design and documentation of information systems in a broad range of industries, including telecommunications, pharmaceuticals, transportation, and manufacturing. A former academic, Richard taught linguistic theory at Colorado State for five years. A Fulbright alumnus, he taught formal syntax and semantics in Poland in 1982-83. Richard has been on the Board of DAMA-NJ since 1993, and is currently the chapter’s Director of On-Line Services.

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Data Model and Integration Strategies for Real-Time Analytics

Kevin Cavanaugh
Vice President of Technology
Unica Corporation

Effective marketing requires judicious use of customer data and coordinated treatment logic across many different operational systems and touchpoints. Unique data & business rule challenges are introduced when distributed operational systems are coupled with the analytical & marketing processing requirements needed to support real-time customer dialogs across these systems. This session explores system architectures and new data model requirements for coordinating outbound and inbound customer treatment strategies based on batch, real-time & event-triggered marketing scenarios across different touch points. Case study examples will be used from recent deployments of real-time and dialog marketing deployments to highlight important lessons learned in their integration into existing high volume production environments.

Kevin Cavanaugh is the Vice President of Technology at Unica Corporation. He is responsible for new product strategy and architecture. He works closely with Unica’s industry-leading customer base to ensure they are maximizing their success in enterprise marketing using the Affinium Suite. With more than 18 years of experience successfully delivering marketing and engineering solutions to the manufacturing, telecommunications, retail and financial service industries, Cavanaugh has an in-depth knowledge of intelligent systems and CRM technologies.

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MODEL-DRIVEN ARCHITECTURES
OR ARCHITECTURE-DRIVEN MODELS:
Thoughts from a Panel of Experts

Michael Brackett & John Zachman (Moderators) Panel of Experts TBA

Several decades ago database management systems were evolving and data modeling was in its infancy. One concept that emerged during the early days of data modeling was canonical synthesis. Individual data models were prepared and, according to canonical synthesis, could be easily plugged together to make an enterprise-wide data architecture. Most of us know that concept has not resulted in any viable data architectures.

An apparently new concept has recently emerged which is generally refereed to as model-driven architectures. In many respects it is nothing more than canonical synthesis with a new name, and like canonical synthesis, has not produced any enterprise-wide architectures. The wide disparity in data models, and data modeling techniques, simply prevents them from being connected to form a consistent data architecture.

Another concept that emerged several decades ago is the Framework for Information System Architectures. This concept promotes a framework consisting of a set of architectures for each column, each of which is composed of a set of models for each row in the column. The phrase 'a complete set of representations, enterprise-wide, horizontally and vertically integrated, to an excruciating level of detail' is well-known today.

A common architecture concept directly supports the Framework concept. One enterprise-wide architecture supports each column in the Framework. All models within a column are developed within their respective common architecture. For example, the common data architecture encompasses everything in the data column, and so on.

Information technology is now faced with two basic and conflicting approaches: model driven-architectures and architecture-driven models. Which is best has not yet been proven conclusively; but, there are many examples and opinions. This panel of experts will present and support their views followed by questions from the delegates

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Methods and Models in Data Architecture

Michael K. Miller
Manager
Cardinal Health

For data management professionals, a major objective is aligning the database environment with the needs and goals of the business. Real-life methods exist that help to ensure a database architecture that is an implementation of the business objectives and strategies. This presentation will combine data architecture methods/practices, the Zachman Framework, and use of an Enterprise Data Model. The Zachman Framework itself is methodology-neutral and it is up to the data management professional how to implement it. The presenter will provide examples of models in each cell of the Zachman Framework data column and discuss methods/procedures on how to build each of those models while at the same time incorporating an Enterprise Data Model.

Michael K. Miller is the Manager of the Data Management Group in the Cardinal Distribution IT organization. His background is in general business management, systems development, systems analysis, and IT architecture. He has practical experience with all phases of architecture, methodologies, tools, process management, and data management. In his career, he has had important roles including chief architect, chief data architect, technology architect, methodologist, senior consultant, and development manager. Mr. Miller has been a frequent presenter at DAMA and other industry conferences. He also authored articles for the DRM Journal, the DM Review, and several editions of Handbook of Data Management. He was the first president of the SW Ohio DAMA chapter.

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The Data Analysis Political Toolkit

Amanda McLoone
Business Process Engineering Manager
Intel Corporation

The contributions of a data analyst is critical to successful information systems development. In spite of it's importance, it is often undervalued and sometimes overlooked by organizations. The root cause can be attributed to a limited understanding from the business community and the lack of visible results from data analysts. Note "visible" as the key word. The results do indeed exist, but are not directly obvious to the business. In order to sustain the importance and visibility of data analysis outside the IS organization, a data analyst needs a set of political tools and tactics which complement out purely academic tools. This presentation examines the traditional role of a data analyst and it's evolution to it's current role. It also unveils a toolkit of full of tactics and strategies to address specific business problems regularly encountered.

The business problems addressed are:

The academic data analysis tools that the community uses are of no value if the business doesn't buy into to the importance of the work. A DA must be equipped with political tactics in order to increase the usability of the academia.

Attendees will learn:

Amanda McLoone has over 13 years experience in the Information Systems industry with an emphasis on Data and Business process analysis. She has been employed at Intel Corporation for the last 9 years in a broad range of organizations covering IT, Logistics, Factory Automation, Corporate Quality and Supplier E-Business. She currently manages the Corporate Quality Business Process Engineering and Data Analysis groups. Amanda’s career accomplishments include the original implementation and proliferation of Intel’s corporate shared data environment. She is responsible for achieving significant cost savings through the automation of a major business process. This cradle-to-grave inception of automating Intel’s Capital Equipment Forecasting process and its delivery as Intel’s first business-to-business application was a major breakthrough for Intel’s eBusiness initiatives. Her most recent accomplishment is the adoption of Business Process Quality as a core function within the Corporate Quality Network.

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Banking on Metadata at Allstate

Doug Stacey Team Leader Allstate

Pam Gardell Team Leader Allstate

This presentation will provide an overview of Allstate's metadata management practices. By leveraging the information in Allstate's repository, we will demonstrate how data is gathered using a custom-built suite of tools, integrated, and then circulated throughout the enterprise. Attendees will gain an understanding of the types of data that can be gathered, the means with which to gather it, and just how it could leveraged for their enterprise.

Doug Stacey has been in the IT Industry for over 20 years, primarily in database management. He has published several articles on data related topics and served for four years on the International DB2 Users Group Board of Directors. He currently holds the position of Team Lead for Metadata Infrastructure Support at Allstate Insurance Company.

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Business Intelligence in the Competitive Corporate World

Adrienne Tannenbaum
President
Database Design Solutions, Inc.

Everyone discusses Business Intelligence (BI) and Knowledge Management these days as the way to "seal the competition". In fact, Competitive Intelligence (CI) goes outside of your business to expand you firm's internal intelligence. It would be nice to know "Who is selling what?" "How long does it take for competitors to get a product to market?" "What product development efforts have not made money within our organization?" "How profitable has our potential partner been?" Competitive Intelligence (CI) is the next step after BI.

Believe it or not, most of this information is already available - some externally, some internally, but most important, it is all free! Your underlying metadata simply needs to be tapped. Many organizations re-purchase this data and store it in a place of its own. Others extract data from internal operational systems and put it somewhere else. This presentation will discuss a true story and give attendees an insight into how "eliminating redundancy" may actually be creating redundancy of its own.

Adrienne Tannenbaum is the founder and president of Database Design Solutions, Inc. (www.dbdsolutions.com), a Bernardsville, NJ based consulting firm specializing in database and metadata solutions. She has worked in all facets of database and application development, concentrating since 1990 on the design, development, and implementation of metadata solutions. She is the author of the foremost reference, Metadata Solutions: Using Metamodels, Repositories, XML, and Enterprise Portals to Generate Information on Demand (2001, Addison Wesley) as well as the first metadata oriented publication, Implementing a Corporate Repository (1994, Wiley). She has also developed and currently teaches several public Metadata Solutions seminars. Adrienne Tannenbaum has spoken at many conferences worldwide. She is known for the practicality of her presentations and has often co-presented with Database Design Solutions' clients. Adrienne is a firm believer in keeping metadata where it is used and needed the most. Her Metadata Solution Design methodology supports this objective. Database Design Solutions is known for its ability to provide 'Information on Demand' in even the most complex of situations. Firm specialties include web-based data access and distribution, data warehousing, data analysis, data management strategies, database tuning and administration, and logical and physical database design. Database Design Solutions consultants are organized by industry practice and are well versed in the data issues surrounding pharmaceuticals, insurance, telecomunications, finance, manufacturing, and the public sector.

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Integration Starts with Business … Using Collaboration with a Business-Centric Methodology
for Enterprise Agility and Interoperability

Mike Lubash
System Accountant
Defense Finance and Accounting Service

The presentation will describe how you can use a business integration methodology being applied at the Defense Finance and Accounting Service (DFAS). The journey begins with establishing and outlining your organization’s Vision, Goals, and Strategy for achieving precise communications among your primary stakeholders. Then, the task is expanded to identify and manage your information assets, their associated business metadata, context and ontology. These technology-neutral artifacts become the building blocks for assembling reusable components to be used in coupled communications between stakeholders. Once these artifacts are identified and documented, we can begin the work of obtaining the infrastructure layers to support either the existing “as is” method of doing business or migrate to technology-oriented or business-centric mechanisms to deliver business agility.

The journey is constrained by a Business Centric Methodology that outlines management criteria to guide you through the myriad of choices and trade-offs you will have to make in order to achieve your organizations tailored vision. The result is tailoring your business message communications to your business partners’ desired semantics and syntax. The integrated information architecture can enhance your organization’s performance and agility to deliver the ultimate business metric, “Customer Best Value”.

Mike Lubash is currently assigned to the Defense Finance and Accounting Service Directorate of Information and Technology, Data Architecture. He is the Department of Defense XML Namespace manager for the DOD Finance and Accounting Functional Area. As such, he was instrumental in the development of the DOD Finance and Accounting Data Model (DFADM), DFAS Process Model, (DFAPM), which supports the departments data management program, architecture and internal DFAS programs like the DFAS Corporate Database, DOD Standard Disbursing System, and System Inventory Database. In addition, he has worked on integration efforts with the DOD Acquisition Community, Integrated Finance and Procurement Data Model (IFPDM) and DOD Personnel Data Model.

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Physically Implementing Universal Data Models to Integrate Data

Len Silverston
President
Universal Data Models, LLC

How can generic or “universal data models” be practically implemented in organizations? This presentation will share several proven alternatives for physically implementing universal data models in order to better manage and integrate data. Len Silverston will show how to convert one of the most critical universal data models from his “The Data Model Resource Book” series into viable physical database designs. He will offer various alternative physical database structures for this data model that can and have been implemented by numerous enterprises to provide significant business value to their organizations.

This session is extremely important because it provides practical and proven solutions to help data management practitioners integrate data within their organizations. Participants of this session will gain:

Len Silverston is a consultant, lecturer, and pioneer in the field of data management. He has devoted the last 20 years to helping organizations effectively manage, integrate and utilize information by developing quality data models, data warehouses and databases. He is the author of the best-selling “The Data Model Resource Book” series (Wiley, 2001, http://silverston.wiley.com), which describes over 230 reusable data models, some of which are now licensed worldwide by Microsoft. Mr. Silverston's company, Universal Data Models, (www.universaldatamodels.com), provides consulting, training and software to jump-start data modeling and data warehouse design efforts while increasing design quality and facilitating data integration.

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OK, So What Exactly is a Data Model, Anyway?

David Hay
President
Essential Strategies, Inc.

Yes, many of us in DAMA are involved in “data modeling”. The problem is, there are almost as many different views of what that means as there are people in DAMA. The time has come to set out some basic definitions. That is what this presentation will do. Looking at John Zachman’s “data” column, which techniques are appropriate for each row, from the Planners through the Designers?

The presentation will address conceptual, logical, and physical models, data model views, object models, and whatever else comes along. It will discuss the various notations as well, and the relative advantages of each for different purposes. It will attempt to sort this all out and provide a clear vision of how all these elements relate to each other.

David Hay: In the Information Industry since the days of punched cards, paper tape, and teletype machines, Dave Hay has been producing data models to support strategic and requirements planning since the mid-1980’s. He has worked in a variety of industries, including, among others, power generation, clinical pharmaceutical research, and all aspects of oil production and processing. He is the founder and President of Essential Strategies, Inc., a consulting firm dedicated to helping clients define corporate information architecture, identify requirements, and plan strategies for the implementation of new systems. Dave is the author of the book, Data Model Patterns: Conventions of Thought, and Requirements Analysis: From Business Views to Architecture.

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Who's on First - 'Data' or 'Process'

Sheila Jeffrey
VP - Technology Services Architecture
Wachovia

This presentation will explore the relationship between data and process (with reference to the Zachman framework), and their amalgamation into ‘objects’ and, now, Web Services. It will discuss the problem of making data analysis and modeling relevant in the real-world context of solving business problems today, with suggestions of why this is so difficult. Understanding how data interacts with the processes that create and use it will suggest approaches that may allow data analysts and modelers to increase their effectiveness. The importance of process modeling as a communication tool and scope management technique will be discussed. The traditional marriage of process and data in the ‘object’ will be briefly discussed, and its more recent dynamic distribution as Web Services, with identification of some limitations of these approaches. In conclusion, this presentation will recommend that improved process understanding can increase the relevance and value of formalized data analysis and modeling activities, and reaffirm the persistence of the ‘data layer’.

Attendees will understand the relationship between data modeling and process modeling, and the strengths and limitations of each technique in solving business problems. The presentation will promote an awareness of how to frame the contributions that data modeling and data architectures can deliver in the broader architectural context. The goal is to provide attendees with knowledge that will help to establish the relevance of data anlysis/modeling work for their organizations.

Sheila Jeffrey: I am the Technical Architecture Process Facilitator for Wachovia’s Technology Services Architecture Standards team, and a member of their Data Architecture Team. Since joining Wachovia in 1980 as an application manager, I have worked in many roles to promote system architecture, data management, CASE implementation, data modeling and metadata management. In 1998, I helped form an Enterprise Information Management division to link the Corporation’s vertical silos and warehouses. Prior to my current job, I was the Enterprise Information Strategist on the e-Commerce Technology Strategy and Architecture team, specializing in CRM and customer information issues. I have presented at DAMA NorthEast conferences, and the Enterprise Data Forum.

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Case Study: Partnering with Business Process Reengineering to Improve Data Quality

Denise Cartledge
Senior Data Administrator
MetLife

Eileen Ponich
Director, Data Administration
MetLife

Our Disability Claims organization began a Business Process Reengineering (BPR) effort to reduce their cost per claim. A data administrator partnered with the Process Consultant and focused specifically on the data identified with the process steps. The data administrator was able to facilitate a bottom-up data stewardship program to help the business manage its data during the staged implementation of the reengineered business processes. Primary lesson learned: the active participation in the BPR efforts by data administration provided an invaluable understanding of the business issues, complexities and process decision rationales which translates into improved support to the business and their data quality.

This case study touches on data quality, data management and data stewardship and how to incorporate them in an business environment that is challenged with changes that are process-focused.

Denise Cartledge has a MBA in Computer Information Systems from California State University, Hayward. Denise's career has included over thirteen years in systems training, facilitation of various aspects of the SDLC, data administration and architecture, and business analysis in various industries including government and financial.

Eileen Ponich has over twenty years of experience in information technology. She has MS, Computer Information Systems from Bentley College, Massachusetts. She currently manages a group of data architects for a large financial institution.

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PANEL: Meta Data Convergence

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Stuart Wiebel Consulting Research Scientist, OCLC Office of Research Director, Dublin Core Metadata Initiative

Sridhar Iyengar Distinguished Engineer, IBM Chief Architect, MOF and XMI, Object Management Group

What would happen if a data manager and a document manager got together to talk about meta data? Unfortunately the conversation would stall quickly, because despite using the same term “meta data” in their work, there is surprising little common ground between them. The document manager deals with unstructured or document data, and the data manager deals with structured data. If you added a video librarian and a geospatial specialist to the mix, it would be a Tower of Babel in no time.

Historically there has been very little co-ordination in meta data efforts or standards between disciplines, but that situation is changing, and there is much to learn from each other. This session brings together the leaders of the new standards initiatives for each group – the Dublin Core initiative (the guru of librarians and documentarians) – and the Object Management Group (for the structured data community).

Stuart Weibel has been in the OCLC Online Computer Library Center Office of Research since 1985, and in that time he has managed projects in automated cataloging, document structure analysis, electronic publishing, and Uniform Resource Names (URNs). Since 1994 Stu has been convener of the Dublin Core Metadata series of international workshops and conferences. He is currently director of the Dublin Core Metadata Initiative, hosted in the OCLC Office of Research. DCMI is an open, international, consensus building organization focused on development of cross-disciplinary metadata standards for the Web.

Sridhar Iyengar, is a Distinguished Engineer at IBM Corporation and previously led the technology research direction for software products at Unisys. He is the chief architect of the OMG Meta Object Facility (MOF) and the OMG XML Metadata Interchange (XMI) which together with UML forms the core of OMG Modeling and Metadata architecture - now a central part of the OMG Model Driven Architecture - MDA. Sridhar has directly influenced all the major modeling and metadata standards from OMG including MOF, XMI, UML and CWM in diverse areas like application development, application integration and data warehousing. Sridhar is one of the primary drivers of the OMG Model Driven Architecture Initiative. One of his pet projects is the integration of UML, MOF and all the evolving metamodels at OMG and elsewhere to maximize the benefits of MDA. He has a master's degree in computer science and is a frequent presenter in industry conferences on topics of modeling, metadata, databases, component software and distributed object technology.

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Vision Accomplished: Metadata Repository to Single Source Directory

Madeleine Lord
Data Adminstration Project Leader
Boston Federal Reserve Bank

This presentation will describe the Metadata Repository and Single Source Directory projects at the Federal Reserve Bank in Boston, which are combined under the Information Data Architecture initiative launched in October 2001. By April 2003 the Boston Metadata Repository will have been in production for a year, and a Single Source Directory pilot will have reference codes and employee information loaded and accessible.

This presentation will cover the story from selling the vision to management, to the design and implementation of the Repository and Single Source Directory. It will include critical design elements, process steps, software and hardware choices, resource allocations, how training was managed, and how the deliverables were and continue to be user requirements driven.

The attendees will learn how to collect, manage and use metadata intelligently, cost effectively and strategically. They will learn to distinguish between Technical Metadata and Business Metadata, how to design a system to promise trustworthiness in both. They will also hear about real benefits experienced at the Boston Fed in an ongoing project.

Madeleine Lord, has worked in technology for 17 years. She has worked as a Data Administrator or in the related field of Data Warehouse Specialist for the past twelve. She managed the Enterprise Data Model and Process Model initiative in a Utility Company in the late eighties, and is currently the Data Administration Project Leader for the Federal Reserve Bank in Boston. She wrote her Masters thesis on the topic of Metadata and its importance to corporate strategies. She has presented to Boston DAMA meetings on the topics: 'Repository on a Shoestring' (related to project at the Utility Company) and recently on 'A Failproof Data Warehouse Load System'.

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Modeling Information Flow: Turning the Assembly Line into an InfoMatrix

David Loshin
President
Knowledge Integrity, Inc.

Most legacy information applications operate in an assembly-line fashion, creating “processed information” in isolated stages the same way that cars are manufactured. Factory-style processing creates artificial barriers to the effective sharing and use of information, leading to lost opportunities and decreased competitiveness.

The first step in turning this linear use of data into an information matrix is understanding how information objects flow through your processing. This presentation will discuss an abstract representation of information flow, and then explore ways this model can be exploited when integrated with meta data, business rules, and business user expectations.

The attendee will learn how the information flow model can be used to:

David Loshin is the president of Knowledge Integrity, Inc. (www.knowledge-integrity.com), a consulting and development company focusing on Business Rule-based information validation and customized Business Intelligence technology and solutions. David is the author of "Enterprise Knowledge Management - The Data Quality Approach" (Morgan Kaufmann 2001), is a monthly columnist for DM Review and www.datawarehouse.com, and is a frequent speaker on Business Rules and Data Quality. David also leads the development of GuardianIQ, a rule-based data validation environment.

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The Associative Model of Data

Simon Williams
CEO
Lazy Software, Ltd.

Today's standard database architecture, the Relational Model of data, is over thirty years old and suffers from some significant limitations, whilst object databases have failed to cross the chasm into mainstream use. The Associative Model of data is a viable and scalable alternative to both that overcomes two fundamental limitations of current programming practice: the need to write new programs for every new application, and the need to store identical types of information about each instance. It also offers a superior distributed data model, allowing one database to be readily distributed over many geographically dispersed servers. Moreover, associative databases may be readily tailored to serve different requirements simultaneously, and different databases may be instantly combined and correlated without extra programming.

Simon Williams is the originator of the Associative Model of Data and has worked in IT for 34 years. In 1984 he founded Synon Corporation, which became the world's foremost vendor of application development tools for the IBM AS/400 platform. In 1998 he founded Lazy Software, of which is currently Chief Executive, to develop the Sentences Database Management System, the first commercial implementation of the Associative Model.