DAMA INTERNATIONAL SYMPOSIUM & WILSHIRE META-DATA CONFERENCE
May 2-6, 2004 – Century Plaza Hotel, Los Angeles, CA USA

CONFERENCE SESSIONS

Tuesday, May 4, 2004
10:15 am - 11:15 am

Entropy, Energy, and Data Resource Quality
Michael Brackett
Consulting Data Architect
Data Resource Design & Remodeling

Data quality is becoming increasingly important for every public and private sector organization, particularly as organizations are being held accountable for the quality of their data. However, there are many different perspectives of data quality ranging from developing databases to integrating data to business information. There are also many perceptions about what quality is and the cost of Quality. This presentation steps back and takes a basic look at quality from the standpoint of physics - entropy and energy. It covers basic topics about:

• How data go bad
• What it takes to maintain data good
• The costs for collecting good data
• The costs of integrating disparate data
• Is data quality really free
• When is quality good enough

Adding Value in a Changing Environment - A Case Study
Duncan McMillan
Enterprise Architect (Information)
Westpac Banking Corporation (NZ)

Boards change, CIOs move on, mergers occur, parents the market evolves - the one thing that is constant is the importance of change and the ability to implement change within an organisation. This case study examines how the approach to Architecture and Information Management within Westpac (NZ), one of the top banks in New Zealand, has changed over the last 10+ years in response to changing needs and environments, where we are now, and what lessons have been learnt. It covers a period in which there have been both significant enterprise successes and failures, a major take-over and varying strengths of relationships with the parent company and between different business units within the company. A number of different Architecture and IM approaches have been used to gain value for the organisation and show that value has been gained. Aspects of these approaches have been cited by Gartner as examples of best practice.

• The Forces
• The Rise and Fall of Towers
• Languages, People, Politics and Money
• The Journey
• Lessons Learned

10 Great Things Which Data Administrators Can Do with Use Cases and Class Diagrams
Susan Burk
Director - Systems Architecture
MassMutual Financial Group

Promoting early definition and understanding of data through logical data modeling, and helping teams understand cross-business-area impacts have been Data Administration's greatest strengths. However, use case modeling and analysis/design class diagramming are here to stay, especially for the development and enhancement of operational systems. For a number of good reasons, logical data modeling should follow use case/class modeling rather than precede it. A challenge for Data Administrators is to reap the benefits from use case/class modeling without having a project or the enterprise lose the unique benefits which DA can provide. By presenting the "Top 10", the following focus areas will be covered:

• Past, Current and Future Role for DA for the develpment of operational systems
• Using the "modeler's eyes" and the DA perspective to support of use case and class diagramming techniques
• Specific aspects of use case and class diagramming techniques which impact data modeling and database development
• Morphing from "Data Modelers" to "Modelers"

A Practical Guide for Inventorying Your Data Assets
Perry Benjamin
Data Management Specialist
The Boeing Company

An inventory of data resources can provide an enterprise with visibility into what data it has, where the data resides, how it is being used, and who is responsible for it. With this visibility the enterprise can more easily integrate its computer applications and respond more quickly to business and technological change. This session will introduce the approach taken to develop and populate the data inventory in use at Boeing Integrated Defense Systems. This inventory system is comprised of a collection of COTS products integrated by a homegrown metadata repository. Both "traditional" and object-oriented/component-based applications are supported.

• Scope and organization of the metadata
• Construction of an enterprise common business object model
• Metadata capture and change management processes
• Components of the inventory system
• Typical use and navigation of the inventory

Are Business Rules Meta-Data In Disguise?
Terry Moriarty
President
Inastrol

The statement “a premier customer is allowed to have up to five unpaid orders outstanding at one time” represents a typical business rule. Further analysis will result in the following questions: “What is a customer?”, “What differentiates a premier customer from any other customer?”, “What is an order?”. In traditional information engineering methodologies, the answers to these types of questions are normally recorded as meta-data in our models. When you look at the natural language statements that are the basis of business rules, do you see the same statements that we normally use in defining an enterprise’s meta-data? The standard definition of the term Meta-data is “Data About Data”. However, this definition leave a lot open to interpretation. This presentation proposes an alternate definition that “Meta-data is the representation of an enterprise’s business rule statements according to a classification scheme that can be readily transformed into business information systems.” Using this definition as its theme, this presentation provides an introduction to the business rule approach and its relationship to meta-data.

• What are business rules
• What is Meta-data?
• How business rule classification schemes relate to traditional modeling techniques
• Integrating the business rule meta-model into an organization’s meta-data model
• Demonstrates how incorporating meta-data structures into an enterprise model can provide the flexibility needed to support changing business rules

Building An XML-Based Data Standard

The state-of-the-art approach for interface development is to use Enterprise Application Integration (EAI) tools. However, the full benefits of an EAI tool can be realized only with a unified understanding of how to describe business data. If you have a standard way to describe the data, you can de-couple systems from each other and eliminate redundancy. The source system's data is first transformed to the Data Standard, and then from Data Standard to what the target system needs. We began to build our own XML based securities data standard (trade, holdings, prices, etc) , since no single industry standard covers all subject areas and on the other hand the applicable standards are far more complex than what we need. Using this data standard, the project team developed 15+ interfaces in a relatively short time. Having gone through this exercise, we hope that as industry standards like SWIFT, FIX and MDDL become more widely used, we will have a simpler migration path. The steps we took to create a prototype data standard include:

• define a Data Dictionary with all the data elements required for our project.
• define a Catalogue of Business Transactions, which defines the data elements involved in each type of business event within our project scope.
• develop a way of generating an XML Schema description of each Business Transaction. XML is an industry standard and is the language of our EAI tool.

From Afterthought to Asset: The Business Value of Data
Jill Dyche
Vice President and Partner
Baseline Consulting Group

As executives continue to scruitinize IT budgets and apply new rigor to strategic business programs, information has evolved from a common denominator to become a strategic business asset. In this session, author and consultant Jill Dyche makes a case for managing data as a corporate asset and describes the business benefits that accompany this strategy. She'll explain why business managers should consider data management as a discrete part of every new project, irrespective of specific architecture or software packages. She will introduce the concept of a corporate Information Center of Excellence- an organization that transcends high-profile business initiatives such as business intelligence and CRM. Jill will present case studies of real-life companies who have put strategic data management to work and reaped the rewards.

Achieving Data Excellence: Roadmap to Success

Data quality, or the lack thereof, has become a hot topic in business, with much attention being given recently to the problems that may arise due to bad data. This is not surprising, given that in 2001, The Data Warehouse Institute estimated that dirty data cost US businesses $600 billion. Despite efforts by organizations to eliminate bad data, however, widespread problems still exist. While much attention has been given to defining data quality and to the impact of poor data on the business, less attention has been given to the specific processes involved in improving data quality. Data Quality Improvement (DQI) to achieve data excellence is the focus of this presentation. Using a data life-cycle approach, the presenters will demonstrate clear, concrete steps organizations can take to improve data quality at all life-cycle stages: capture, storage, and access. Those attending this presentation will learn:

• The life-cycle view of data excellence
• Strategies for achieving data excellence at all life-cycle stages
• Three primary areas in which DQI initiatives should focus
• How to sell a DQI to top management

The Training and Mentoring of Data Analysts
Janet Siebert
Data Architect
Data Pantheon

Effective data analysis is essential to successful IT implementations, operations, and troubleshooting. Yet, data analysis is not a subject normally taught in universities, nor is it a subject of many books or articles. Drawing on her background as a professional educator and data analyst, and integrating material from interviews with other high-performing data analysts, Ms. Siebert discusses the fundamentals of data analysis. Additionally, the discipline of data analysis is examined against the background of relevant theories of education and educational psychology. Topics discussed will include:

• What are the core competencies of successful data analysts?
• How do we deliver more effective data analysis through training and mentoring?
• What can we learn about improving data analysis by examining educational theory and practice?

Verbalizing Business Rules
Terry Halpin
Professor and VP (Conceptual Modeling)
Northface University

Although business rules may be implemented in many ways, they should first be specified at the conceptual level, using concepts and language easily understood by the business domain experts who are required to validate the rules. Business rules come in many varieties, such as constraints and derivation rules, and may be specified using graphical and/or textual languages. The focus of this presentation is on expressing a wide variety of business rules in a high-level, textual language that has been designed for expressibility, clarity, formality, generality, and localizability. The rule verbalization techniques and patterns are illustrated using practical examples. Alternative verbalization approaches are identified to allow the techniques to be applied to business models diagrammed in Entity Relationship, Object-Role Modeling, or Unified Modeling Language notations.

• Using positive, negative, and neutral verbalization patterns for rule validation
• Relational-style verbalization vs Attribute-style verbalization
• The use of context for verbalization of complex rules and rule sets
• Verbalizing rules involving projections over multiple associations of any arity
• Verbalizing reaction rules
• Making verbalizations formal and executable

Metadata Management Converges with Business Modeling
Joshua Fox
Sr. Software Architect
Unicorn Solutions Inc.

It is valuable to have metadata resources in a repository. However, metadata identifiers tend to be cryptic, oriented towards application developers, and unable to convey relationships between various enterprise assets. Likewise, business models help analysts and business leaders understand an enterprise. But in many cases, the models become disconnected from reality; when models are not used by technology implementers, they soon cease to accurately reflect the enterprise.

Mapping metadata to a central model combines these two approaches and brings out the best in both of them. Metadata gains semantics, and models gain a firm grounding in the actual enterprise infrastructure. This results in improved quality and agility in the management and development of information assets. Existing assets can be reused, and redundant assets can be eliminated. When the models are synchronized with the IT infrastructure, the enterprise can unite on a shared understanding of business concepts and processes. In this way, linking business models and metadata in tandem increases the value of both. The presentation will be based on real-life case studies implementing an integrated metadata/modeling architecture in enterprises.

• The relationship between business models and metadata repositories, and the integration points between them.
• A methodology for providing direct business value while implementing integration in small steps.
• The business value gained from this integration

Successful Meta Data Management in Complex Siloed Systems
Sean Goggins
Principal Consultant
Ciber, Inc.

Manufacturing, medical research and the emerging “informatics” labeled disciplines are most often substantially concerned with the existence of inconsistently labeled and classified data across 20 or more small “systems” that compose an organization’s complete super-system for data creation and analysis in these areas. It is also common for disparate versions of systems like this to be deployed in 10 or more specific instances across such organizations or, in some cases, customers. Traditional approaches to data management and meta data management provide a strong but incomplete foundation for successfully adding value to systems of this scale. Participants in this session will gain a comprehensive, “Big Picture” view of the challenges to consider in the development of a metadata management strategy for organizations with complex systems that support real time manufacturing, clinical research and informatics oriented domains. Specific, proven “Tools of the trade” covered in this hands on workshop include:

• UML 2.0
• XMI
• MOF
• BPXML

XML Tools Comparison:
Cutting through the hype - what works for Data Management?

Much of the hype generated around XML comes from and revolves around the various XML tools and XML features of existing tools. This session will demonstrate the functionality of various classes of XML tools including:

• XML editors
• Translators
• XML parsing technologies
• Servers.

Attendees will understand how they can apply these technologies in support of their day to day data management activities.

Database Trends: The DBMS Landscape Circa 2004
Craig Mullins
Director, Technology Planning
BMC Software

Database Management Systems are at the heart of most modern computer applications. Whether you use DB2, Oracle, SQL Server, or some other DBMS, chances are you rely on a database to store, protect, and serve your organization's data. But what is a DBMS really? Of course, there is a simple answer at the core that most of us know - but database technology is changing very rapidly. This presentation will take a look at the major trends impacting DBMSs in order to help clarify all of that new stuff your DBMS does - or will do very soon.

1:45 pm - 2:45 pm

Using an Enterprise Portal to Drive Global Data Architecture at Citigroup
Denis Kosar
VP Data Architecture
Citigroup

Today, the US Government has added more business pressures to the already changing economy. Legislation such as Sarbanes Oxley and Basel II have changed the way corporations in the Financial Services industry conduct business. This has had a major impact on the way that IT has to design, maintain and report their corporate data. This presentation will show how a metadata driven strategy has helped Global Data Architecture at Citigroup meet these business drivers and challenges. Using an Enterprise Portal to market data modeling, best practices, reference data and reverse engineering services Citigroup has made the role of Global Data Architecture not only successful but has helped them to flourish across the enterprise.

• Overview of Citigroup organization structure
• Roles and responsibilities of Global Data Architecture
• Citigroup's Metadata Framwork and Strategy

International Cross-Enterprise Shared Data
A Framework for Business Implementation

The goal of securely sharing sensitive data across enterprises and across international boundaries is fraught with security, commercial and regulatory pitfalls. This presentation describes the significant progress being made by Defence primes with transatlantic governments support to enable large Defence contracts to benefit from real e-business advantages whilst ensuring compliance of different nations respective national security, data protection, privacy, export control, Sarbanes-Oxley regulations. The description of the Framework and associated guidance will highlight how developments in:

• identity management (of personal and assets)
• secure cross enterprise logical information architecture,
• multi-national export control compliance business rules,
• applying DRM

...can be used with a revolutionary collaborative risk assessment methodology to share data securely and profitably. The talk will close by detailing areas in which optimization of data architecture, meta-meta data developments and data stewardship are needed in order to enable maximum business benefit.

Enterprise Data and Process Modeling for the
Telecommunications Industry — a case study using the E-TOM model
Robert Mattison
CEO
Excellence In Telecommunication

In this session we will review the way that the Telecommunications industry E-TOM (Telecommunications Operations Model) was utilized to create an entire enterprise reporting, data warehouse, data mining and operational process quality infrastructure for a very large, start-up telecommunications company.

Yes, it is possible to do it right the first time, and this case study will you how it was done!

The Role of Metadata Management in the Construction of a Successful Data Warehouse
Kris Morris
Specialist IT Design - Enterprise Information Management
3M Company

3M’s large and diverse Data Warehouse requires a robust, active metadata (MD) repository. It's critical to its success to store MD, supporting the entire construction process: data design, analysis, development, and testing & quality assurance. 3M’s MD solution is a best practice in many ways:

• Manages data legacy from source system through each transformation.
• Captures subject areas data structures.
• Audits the DW, detecting undocumented changes.
• Provides web reports to DW developers and business users.
• Generates data models.
• Manages ‘canonical formats’ for internal ETL.
• Manages business rules and error conditions.
• Defines tolerance: data completeness and accuracy.

Components of “MD Family”:

• MD Portal
• MD Warehouse
• MD Design Manager (MDM), the UI
• MD Reporting (Business Objects); (e) MD Acquisition
• MD Quality – auditing MD; and (g) MD Engineering (“CASE” tool).

Creative Metadata on a Shoestring!
Bonnie ONeil
President
Westridge Consulting

Learn how to exploit inexpensive software tools to do metadata management in creative ways. Some of the tools presented here include a bibliographic database for rapid text/content searches, “mind mapping” software for content management and brainstorming, and business rule management software. Topics covered will be:

• Tools for requirements gathering and business rule mining
• Capture metadata from existing data in your environment
• Present data in different formats (present data on the web with a single mouse click!)
• Turn business rules into useful metadata
• Involve end users

Metadata: How Far Can it Take Us?
Doug Lenat
President
Cycorp

Prepare to “upgrade” the vision you have for your metadata strategy. After a near 20-year effort to convert human common sense into a form that computers can understand and use, the Cyc Knowledge Base (pronounced “psyche”) has recently emerged into the commercial world. You can think of Cyc as a “super-metadata” engine – providing layer upon layer of additional understanding and context to the specific metadata already in your systems. These extra layers of metadata then open the door for all sorts of new and exciting applications. Cyc is an extraordinary technological achievement will likely change the metadata landscape forever, and this session gives you the opportunity to learn directly from its creator, Dr. Douglas Lenat.

• What is Cyc and the CYC Knowledge Base?
• How does Cyc provide you with metadata?
• How is this qualitatively different from what metadata usually provides?
• How does the layering of more and more metadata help? What changes occur as we add these additional layers?
• Application areas in data management:
  • Integrating disparate databases
  • Data quality
  • Better search and querying
  • Semantic web
  • Security and compliance
    

Assessing BI Suites and Platforms for Performance Excellence
Jonathan Wu
Senior Principal
Knightsbridge Solutions

Business Intelligence (BI) provides individuals with the ability to easily access information for analysis, reporting and decision-making purposes without having to understand the associated complexities of the structured data, technical architecture or transactional systems. Executives and managers need access to information, which ranges from sophisticated cross-functional enterprise analytics to trend analysis and potentially transactional data. This information can hold the key to increased market share, customer retention, and operational efficiency. Through BI and data warehousing technologies, individuals can access information to monitor business activities and performance, which is critical to success and in certain cases survival in today's economy. The audience will learn the functionality of the leading BI suites and reporting technologies, as the session addresses the following:

• Leading Product Vendors
• Product Categories
• Technical Architectures
• Matching Needs with the Corresponding Technology
  

3:15 pm - 4:15 pm

PANEL: Data Modeling is Alive and Well!
Davida Berger, Terry Halpin Graham Witt, David Hay, Chris Date

We live in a world of ERP, packages, short-term solutions, tactile projects and outsourcing. Some organizations have replaced corporate data architecture areas with project teams that include database administrators but may not include data modelers. Others only develop physical models and skip development of the logical model. Is this the best way to proceed? Where does UML, and ORM fit into this type of environment? What happens with project models when a centralized data management area no longer exists? Are short-term project models integrated or simply discarded after a project is implemented? Is there no longer business value in business modeling? In other words is data modeling as we know it a thing of the past. Our panel of experts will address these questions and other controversial areas of concern to today's data modeler.

Enterprise Common Data Architecture - Roadmap to Integration
Daniel Paolini
Director, Data Management Services
State of NJ Office of Information Technology

An Enterprise Common Data Architecture (ECDA) is a collection of related tools and technologies, along with standards and policies and the methodology and the expertise to employ them. The architecture enables real-time operational integration as well as the delivery of integrated analytical data to different communities in the format that each requires. The creation of an ECDA is a major yet essential commitment to any long-term strategic initiative to support data reusability. This architecture forms the foundation for collecting, storing, managing and controlling privacy of and access to data on an enterprise basis. The presentation will discuss:

• The problems and challenges of a legacy environment
• The opposing needs of operational and analytical systems
• The process to create integrated operational systems
• The rational creation of analytical solutions
• How to get IT staff, executive management and business users to see the big picture

Can the Warehousing Center of Excellence implement a Meta Data Repository?
Lowell Fryman
President
Metrics Consulting Corp

This session will explore the real-world implementation of an enterprise meta data repository by the Center of Excellence (CoE) for an international automobile-manufacturing firm. Many companies are implementing the model were the CoE is responsible for Pattern definition, tools, practices, and providing guidance to application teams. However, the CoE is not responsible for implementations. In that case how can an enterprise meta data repository be implemented and managed? Attendees will be presented with the case study of how this issue was resolved by this an international automobile manufacturing firm.

• What were the options for enterprise meta data Vision, Goals, Objectives and ROI
• How to build and engage the cross-functional evaluation team
• What was the meta data tool evaluation process
• How to develop the evaluation criteria and weighting
• How were the product scored and the team achieve a recommendation consensus
• What is the enterprise meta data architecture and how was it integrated with the application development environment
• What were the implementation challenges and how they were resolved

Working with the Dublin Core Metadata Standard
David White
Lead Architect, Metadata
BellSouth Corporation

The Dublin Core is fast becoming the standard representation of metadata that for representing the semantic meaning of web-based documents. This presentation will introduce the basics of the Dublin Core initiative and how your organization can implement this standard.

• Overview of Web based Metadata
• Dublin Core Schema, Elements, Qualifiers, Expansion
• Dublin Core within HTML (Metatag)
• Dublin Core within XML (RDF)
• Dublin Core Syntax
• How BellSouth is using Dublin Core currently, and how we will be using it in future
• Recommended starting points for working with the standard

Metadata and IT Service Management
Charlie Betz
Technical Consultant
Best Buy Corporation

What is configuration management? What is the difference between incident and problem management? What is the purpose of a capacity planning capability? These IT process areas have increasingly formalized definitions, based on the emerging general area of IT Service Management and its flagship standard, the UK-based Information Technology Infrastructure Library (ITIL). ITIL has been sweeping US Fortune 500 corporations over the past 2 years and, while it never mentions the word “metadata,” calls for something termed a “Configuration Management Database” (CMDB). What is the relationship between this and the concept of a metadata repository? There are significant overlaps and opportunities for both synergy and disharmony. This presentation will discuss in detail the ITIL concepts as they relate to metadata. In particular, the highly generalized data model of the ITIL CMDB concept will be critiqued, and richer, more accurate approaches discussed. The following points will be covered:

• History and purpose of ITSM and ITIL, and the major players involved
• The major IT process areas as described by ITSM
• What is a CMDB, and how does it contrast with a metadata repository
• How process-centric standards (ITIL, CMM) and information-centric standards (OMG, DMTF) might be related
• The benefits of integrating data metadata and configuration management
• Vendor directions in these areas

Enterprise Information Architecture for Unstructured Data

The development of enterprise data architecture is typically viewed only from the standpoint of sharing common, structured data. However, for many corporations, unstructured data comprises the majority of the information assets, and the development of an enterprise architecture around unstructured data is an important component of the overall enterprise information strategy. This presentation will focus on the approach being used to develop an information architecture for unstructured data, the unique challenges that the unstructured data environment poses, and the approach and techniques used on a project currently underway at a large, global pharmaceutical corporation. The key areas of the presentation will focus on:

• The challenges of developing enterprise information architecture for the unstructured content world.
• Content classifications and hierarchies, and the relationship to an enterprise information architecture.
• Elements of content analysis that are critical to developing enterprise information architectures.
• The development of a metadata strategy and implementation to support enterprise information architectures.
• The importance of information architecture for corporate knowledge management (cross-enterprise search and retrieval, taxonomies and categorization).

Data Privacy and Security: What It Is, Why You Need It, and How To Do It
David Schlesinger
Intel Data Policy Governance Manager
Intel Corporation

In an increasingly regulated data environment, Data Administration holds the key to effectively managing HIPAA privacy issues, Sorbanes-Oxley regulation compliance, EU privacy regulations, and other data-content related compliance requirements. This session will show why capturing these data-specific security attributes during data definition and application user-role development will:

• Turn your metadata repository into an active and pivotal element of your information architecture
• Provide unprecedented value to your developers and managers trying to comply with data-specific regulations

The session will present a framework from which to work to define the various types of regulated data, and to capture it in a way that will present itself usefully to both managers and automated security processes. New HIPAA and Sorbanes-Oxley legislation, in addition to new privacy regulation in California and elsewhere, make it imperative that Data Administrators identify the data elements which require special care and security. The proper place to capture this metadata is the metadata repository.

Wednesday, May 5, 2004

8:30 am - 9:30 am

What do you do when the CIO says "forget the gurus - go save me some money!"
David Newman
Senior Director of Enterprise Data Management
Radio Shack

David Newman at RadioShack has that challenge, and is creating a comprehensive information asset management environment that will challenge some of the conventional wisdom around the role of today's data management organizations. He is responsible for defining and implementing a comprehensive information management program in a tight economic climate and an increasingly competitive industry. He will introduce a new value proposition for Enterprise Data Management, including:

1. Compliance
   Teaming with Internal Audit to help your CIO and CFO, especially in areas such as SARBOX: How to assist Internal Audit functions with: Meta Data Management; ETL; Data Quality Management; and Data Model Management
2. Helping Your CIO on Operational Efficiency
   Identify inefficiencies in current application portfolio, such as redundant point-point interfaces and how to create common views for a Single Version of the Truth.
3. Architecting a better way - EDM support for EAI
   Migrating to lower cost platforms, establising a common data layer and EDM'r role in Enterprise Data Warehousing

Hear about RadioShack's strong foundation for Information Asset Management in areas such as: Enterprise Data Architecture; Data Governance, Change Management, Technology; Organization and Business Application Alignment and how these can be applied in a practical, cost-conscious manner to achieve significant benefits to the organization.

UML for Database Design
Terry Quatrani
UML Evangelist
IBM

The Unified Modeling Language is the standard language for visualizing, specifying, constructing and documenting all of the artifacts for a software system. Finally database modelers can now reap the same rewards from using the Unified Modeling Language as application developers have been doing for years. Application and database modelers can now speak one language - UML. No longer are database analysts, modelers, and designers relegated to the tail end of the development lifecycle. Now database designers can participate from the inception of the project, helping shape those early decisions that often have a critical impact on the system’s data. Also, being able to link together the object and data models, and thereby improving the understanding of both, helps yield higher quality systems. Attendees will learn about:

• The basic UML diagrams and how they can be used for data modeling
• The UML profile for data modeling
• The relationship between the UML diagrams and conceptual, logical, and physical data modeling
• The benefits of each UML diagram to the database designer
• How UML helps to jumpstart their database design

Success in a Storm: A Case Study on Wyeth Consumer Healthcare Data Architecture
April Reeve
Associate Director
Wyeth Consumer Healthcare

While many corporations were trimming or eliminating their IS Data Architecture functions during these last two years, Wyeth Consumer Healthcare continued to invest and grow its Data Architecture team. Data Architecture had become a key contributor and trusted advisor to their client organizations while other Data Architecture organizations have struggled to prove their value within Information Technology and their corporate organizations. This presentation will discuss the factors and behaviors that have made Data Architecture a success at Wyeth Consumer Healthcare.

• Why did the Wyeth Consumer Healthcare Data Architecture organization continue to grow even during a period of organizational downsizing?
• What were the key differentiators between this organization and traditional approaches taken by architectural groups?
• How did Data Architecture become a trusted advisor?
• Why did there remain an independent IS Architecture organization in Wyeth Consumer Healthcare while other infrastructure organizations were being combined into shared services for the entire Corporation?
• What are the benefits, and struggles, of being a small organization within a much larger organization?
• How is the time of the Data Architecture staff apportioned to various functions?
  

Meta Data Exploitation for Financial Gain
Christine Craven
Customer Insight Development Programme Manage
Abbey

Increasing competition, strategic partners, mergers and acquisitions represent some major challenges for the organisations of today. However, effective development and exploitation of meta data can significantly facilitate information integration requirements associated with these challenges and at the same time provide substantial financial benefits and improved customer service.

This presentation will provide practical examples of how Abbey has developed and exploited its meta data to improve its Cost : Income Ratio and eliminate some major customer service eyesores. Testament to the success of this particular metadata effort is that Abbey received a Wilshire Award for Metadata Best Practices in 2003 (Highly Commended).

The Ins and Outs of Semantic Integration
JP Morgenthal
Chief Services Architect
Software AG

Semantic integration is a powerful superset of data and systems integration. It allows us to integrate data and systems behind an abstract representation that provides additional context. JP will discuss how semantics allow machines to understand how data and systems relate to one another and then provide abstraction, reusability and agility for future application development. He’ll demonstrate the critical importance of metadata and explain how ontologies improve the capability for semantic integration by providing classifications that help to create order and improve the understanding of relationships between entities. JP will present real-world applications of this technology and attendees will leave with a greater understanding of:

• The power of semantic integration
• The critical role of metadata in semantic integration
• How ontologies improve the capability for semantic integration
• XML and Web Services as the standards driving dynamic integration
• New approaches to delivering semantic integration to the enterprise

XML vs Relational: Comparisons and Contrasts
David Plotkin
Data Quality Manager
Well Fargo Bank Consumer Credit Group

This presentation will compare and contrast XML vs. Relational data management and technologies. Many of the differences between them are quite clear, and their advantages and disadvantages obvious. However that doesn't necessarily make it easy to choose between the two, as trade-offs will always exist. David Plotkin is a seasoned practitioner who has worked extensively with both technologies in a variety of corporate environments. He will identify the principle differences and similarities so that you can better understand each one, and to enable you to make better architectural decisions in future.

• What is XML from the data practitioner's view
• The basic assumptions for relational data
• Relational metadata schemas and the repository
• XML metadata schemas and the repository
• Relational architecture vs. XML architecture
• What relational is really good for
• What XML is really good for
• Querying XML vs. querying relational
• Managing change (flexibility) for relational vs. XML
• Cost considerations
• Comparing data integrity
• "Future-proofing" your decisions

The Human Side of Data Modeling:
Proven Techniques for Improving Communication With Subject Matter Experts
Alec Sharp
Consultant
Clariteq Systems Consulting Ltd.

Above all, data models should be viewed as a communication vehicle - a "lingua franca" - among different stakeholders, including decision-makers, content experts, analysts, and designers. Unfortunately, the communication often gets lost - we data modelers can get so proficient in our world of abstraction, generalization, and various forms of ER, OR, or class modeling that we forget that this is not everyone's natural way to converse. The result - goggle-eyed, confused, or frustrated subject matter experts, and therefore, inaccurate models. Luckily, experience has shown that doesn't have to be this way - simple techniques, consistently and regularly applied, will go a long way to ensuring involvement, buy-in, and communication. This presentation, based on over 20 years of successful data modeling experience, will describe these techniques and topics such as:

• How to initiate and proceed through a modeling session starting from scratch
• How to initiate and proceed through a session starting with existing models
• Why you should skip the client "tutorial" on data modeling
• The value of regular recap presentations, and how to conduct them
• How to use IPA - "Information Pain Analysis"
• Appealing to all learning styles - visuals, auditories, and kinesthetic.
• Conventions for comprehension - guidelines for data model graphics
• How to develop entity definitions that uncover the surprises
• Using other perspectives to add context - process workflow, use cases, and application logic/business rules

10:00 am - 11:00 am

Challenges for Data Architecture in a Package Environment
Dawn Michels
Senior Data Architect
Guidant Corporation

More and more companies are embracing "off the shelf" software packages to perform their Information Systems functions. Unique challenges to the data architecture discipline abound. Even though companies are turning to packages, it doesn’t mean data modeling, data design, and documentation aren’t important. The approach is just a bit different. Many of the skills possessed by a qualified data architect, still add value to this challenge. This presentation will highlight some of the specific challenges as well as some techniques for sustaining a valued data architecture function in a package environment.

• Understanding the data layer of software packages
• Integrating corporate data models while working with disparate packages.
• Showing continued value of data analysis
• Discussing who should be involved in the data modeling work
• Controlling "run-away" programming
• Defining deliverables that add value with package implementations

Creating a Global Master Data Organization and Process: A Real World Case Study
Terry Haas
Director, Customer Analytics
Air Products and Chemicals, Inc.

Air Products and Chemicals, with over $5B in sales in chemicals and specialty gases, was implementing SAP worldwide. The first go-live highlighted the need for a radically different approach to data management. This presentation will describe how senior management came to this conclusion, and the steps to define the process and establish the new dedicated organization. The result of this 18 month journey is a new process for data management led by a single Global Process Owner with Data Stewards in the three major regions managing dedicated teams of data administrators. As an example, in the North America legacy environment over 140 people could update parts of customer master and pricing data – in the new world, this work is done by 10 full time data administrators. Terry Haas led this project and is currently responsible for the function. While the result is now a success, there were some missteps and lessons learned along the way that he will share. This is a real life case study in the formation of a full-time data management organization and process.

• Convincing management to change to a dedicated data management organization
• Resolving the politics of moving roles for data management to a separate, full time group
• Defining a workable data management process including service level agreements
• Managing master data management through process and quality measures
• Implementing data quality process as well as data administration
• Defining success

Making Your Entities Behave: Entity Life Histories
David Hay
President
Essential Strategies, Inc.

The characteristic of object classes in object models that distinguishes them from entity types in entity-type relationship diagrams is the specification of their behavior. It seems a reasonable extension to suggest, then, that when entity types representing things in the world are specified in requirements analysis, entity/relationship models could also be extended to represent the behavior of these entity types. The behavior of a real-world entity type, however, is often much more complex than the list of steps that could be captured in the lower third of a UML class box. So, while it is appropriate to want to know what functions are performed around the entity type, the description requires much more than a simple narrative. Enter the entity life history. This is a technique for representing the set of events that affect a particular entity type and the operations that are carried out in response to those events. It represents the complexity of different events and their effects. This paper will present the technique with a set of examples.

• Objects, entities, and behavior in the real world
• A sample data model
• Events
• Event/Entity type matrix
• Sample entity life histories
• Activity Fragments and operations

End-to-End Enterprise Data Integration
Toyota's best practices for integrated metadata, data migration and data quality management
John Gonzales
Data Quality Manager
Toyota Motor Sales

In this session, Toyota Motor Sales will describe the best practices it successfully implemented via an integrated data integration suite – enabling them to incorporate metadata into data quality analyses, as well as data migration and transformation logic, and vice versa. Toyota will detail its data integration architecture, and discuss the key benefits it has achieved since the implementation. These benefits include the ability to provide timely and critical information to business experts, as well as data integration and quality analysts. By capturing information about data modeling and architecture, source-to-target mappings, data transformation logic and data validations, Toyota is able to incorporate the results of its data quality analyses into its data migration logic and quickly address potential data anomalies. This session will illustrate:

• How to implement enterprise data integration best practices for metadata, data quality, data migration and data transformation.
• Key technical benefits obtained by Toyota via their integrated data integration suite, including reduced redundancy of data and processes, increased productivity and lower impact off staff turnover.
• Key business benefits obtained by Toyota via their integrated data integration suite, including faster analysis of corporate data, more profitable decision-making and increased confidence in corporate data.
• The do’s and don’ts of implementing end-to-end data integration.

Proactive Metadata-Driven Information Quality
David Loshin
President
Knowledge Integrity, Inc.

As more data is used for multiple purposes across an enterprise, the perception of information quality depends on the information consumer and the corresponding application context. Fitness for use is directly related to compliance with the expectations of how data is used by the information client, and being able to measure compliance with those expectations can provide an objective assessment of the quality of the data. For any data set, many consumer data quality expectations can be refined into formal relational constraints to be incorporated as metadata. In turn, these constraints can be used as business logic for proactively identifying noncompliant data instances before they are integrated or committed. This workshop focuses on a process for successively refining naturally defined data quality requirements into formal metadata constraints and rules, as well as techniques for using these rules as a component of a proactive information quality assessment and monitoring program. Attendees will learn:

• Successive refinement of data quality expectations
• A syntactic framework for formally defining data quality constraints
• Managing data quality constraints as metadata
• A technique for transforming data quality rules into operational code

A Checklist for Building a Taxonomy
Malcolm Chisholm
President
Askget.com Inc

Taxonomies are increasingly important in knowledge management, but are more frequent than is often realized, since many reference data tables are in fact taxonomies. However, building a taxonomy can be surprisingly difficult. This presentation walks through a checklist of items that need to be addressed for a taxonomy to be successfully implemented. Issues that can arise from not dealing with each item in the checklist are examined. Assuring the internal consistency of taxonomies is also explored. The checklist also highlights the limitations of taxonomies.

• Governance of taxonomies, both during their design and after their implementation
• Strategies for classifying the subjects of a taxonomy.
• Managing the different contexts in which a taxonomy can be used.
• Managing evolution of the taxonomy over time.

PANEL: Data Management Imperatives for Sarbanes Oxley Compliance
Tim Mawhinney, PricewaterhouseCoopers
Christine Craven, Abbey
Legal representative TBA

This presentation will take a look at the requirements of Sarbanes Oxley and how you in data management organization can effectively help your organization meet its the compliance requirements. It will look at how various organizations are meeting their compliance needs through data quality and metadata programs, and how you can learn from these efforts. For some organizations there may be a requirement to disclose deficiencies in the design or operation of internal controls within their compliance process. Because many companies rely on their enterprise data as the foundation of theses internal controls, there will be a growing need for the technical staff to understand the business ramifications of these initiatives.

• Data Requirements for Sarbanes Oxley
• Ramifications of data quality and business semantics for compliance
• Role of metadata in compliance
• Is it too soon for best practices to have emerged?
  

11:15 am - 12:15 pm

Practical Experience with Enterprise Data Modeling
John Sykes
Manager
The Vanguard Group

Since 1999, The Vanguard Group has actively pursued the deployment of enterprise databases. These databases now provide the back-bone for Vanguard's award-winning website, as well as new CRM applications being deployed company-wide. The ongoing Enterprise Data Modeling Effort has been critical to the successful roll-out of these applications. This presentation will share some of our experiences, successes and pitfalls, with the session attendee, including:

Successes:

• Adopting a maturity model for enterprise database evolution to establish a vision and temper expectations.
• Setting clear and measurable objectives for the data modeling team.
• Utilizing Reverse-Engineering to jump-start models.
• Adopting "structured agile" data modeling techniques.
• Embracing continuous process improvement.

Pitfalls:

• The desire for "top-down modeling".
• Dealing with conversion and interface teams.
• Analysis Model (Class Diagrams) vs Logical Data Model Dilemma.
• Insufficient Metadata for knowledge sharing.

Enterprise Architecture: A Strategic Approach to Improving Data Quality and Restructuring Information Management
C. Lwanga Yonke
Manager, Information Delivery and Quality
Aera Energy LLC

This presentation describes how Aera is using Enterprise Architecture to achieve data quality and fundamentally restructure the way it manages information. Enterprise Architecture Planning provided a rigorous assessment of the current state and clearly defined the target architectures. The subsequent implementation program is defined by an ambitious system development schedule and supported by a comprehensive Data Quality process. It is steadily delivering the desired state. The presentation discusses the essential components of Aera’s approach and examines the critical success factors identified. Enterprise Architecture has proven to be a superior means to align business and IT, integrate people, process and technology, and reduce the costs of information management. Topics include:

• Defining an Enterprise Architecture Plan
• Using the Zachman Framework as a guide
• Blending Enterprise Architecture and Data Quality
• Choosing the right system development methodology
• Implementation challenges and results
• Maintaining constancy of purpose over the years
• Real-life successes, pitfalls, trade-offs and lessons learned

The Table Management Distribution System:
Air Mobility Command’s Reference Data Success Story

The Table Management Distribution System (TMDS) is an Air Mobility Command (AMC) unique, on-line information system that supports centralized control, maintenance, and distribution of reference data. TMDS provides AMC with a single, integrated, consistent source of reference data and distributes that data to the operational systems as changes occur. Operational systems use this data to validate specific data fields in operational information transactions. TMDS solves a major gap in the operational command and control and transportation systems by ensuring reference data are the same across the enterprise. In addition, TMDS provides synchronized distribution, ensuring the systems have access to updated reference data at the same time. In the past, dissimilar reference data was a primary cause of rejected messages between systems, causing disjointed information for decision-makers. Since the systems have implemented data value checking and TMDS has supplied data to the operational systems, the error rate due to data integrity dropped from 50% down to 7%.

• The background of TMDS and why it was created
• The current process TMDS follows in managing reference data for AMC
• TMDS success stories
• How TMDS enables interoperability within AMC, the Air Force, and the Department of Defense

Pragmatic ways of getting ROI on you metadata investment
Wilfred Ulmer
Data Architect
WCB Alberta

Ensuring that the information user has the access to the right metadata that is accurate, complete and timely is critical for any organization. This must be managed in a pragmatic fashion to ensure continued budget support and user compliance to standards. This presentation will identify what has and what has not worked at the WCB to obtain return on investment of the meta data repository (MDR) and how we are addressing changes to CASE tools, database managers with the MDR. This workshop will provide a live demo of the repository showing how the WCB has extended the base product to address metadata change management. These approachs can be applied to any custome built or purchase MDR.

• How the metadata management strategies were implemented in a world of budget cuts.
• Live demonstration of approaches implemented in managing the synchronization of metadata from various meta stores including COGNOS, multiple CASE tools and database managers.
• Strategies used to work in a collaborative development approach with software vendors to manage the upgrade of scanners and buses required for provisioning metadata.
• Roles and Responsibilities of the various agents
• Strategies to ensure compliance to information management standards.

Efficiently Implement Data Lineage and Impact Analysis in 100 days
Myles Chapman
IS Leader - Data Management
Best Buy Co., Inc.

Data Lineage and Impact Analysis are key deliverables of Data Professionals. Sarbanes-Oxley requires companies to “collect, process and disclose the information required in the company's [financial] reports.” Implementation of Data Lineage allows your auditors to validate the information on is accurate. Many IS shops have aggressive service level agreements to meet. Implementing Impact Analysis aids your development groups providing a roadmap for development and testing of systems. This capability can find hidden dependencies before that key job fails affecting your whole batch window.

Many companies don't implement a metadata repository because there is no perceived financial ROI. Best Buy has implemented a very successful metadata repository that provides Data Lineage and Impact Analysis. This session will cover the common tricks, tips and traps to an successful and efficient Metadata Repository. We will share the secrets to our success, common challenges, work-arounds.

• Data Lineage and Impact Analysis, why is it so important?
• Minimum data required to implement these functions
• Build vs. Purchase. Technology considerations
• Best Buy metadata implementation
• Tricks, tips and traps

Managing Metadata in Oracle
Daniel Liu
Senior Technical Consultant
First American Real Estate Solutions

There are several different ways of managing metadata in an Oracle database environment. Prior to Oracle9i, there are two popular methods to extract metadata from data dictionary. The first method involves querying the data dictionary using SQL statements. The second method involves running Export with ROWS=N, then running Import with SHOW=Y. Oracle9i introduces a new Metadata API (DBMS_METADATA package). It allows database users to easily retrieve complete database object definitions (metadata) from the data dictionary. This presentation will cover different aspects of managing metadata in Oracle database. Attendees will also learn the new way of managing metadata in Oracle9i using metadata API package tool.

Defining the Financial Value of Information
Robert Randall
Senior Consultant
The Intoinfo Consulting Group

Policies and corporate directives on the management of organizational and public information assets have created a new imperative for effective Information Management (IM). However, despite such demands, scarce budgets and no commonly accepted and understood methodology for putting a dollar value on the information asset is impeding information management specialists in private and public sector organizations. Information management professionals are having difficulty convincing executive management of the investment that needs to be made. This presentation will provide practical guidance to help managers place a value on information assets through case studies and tactical suggestions. The presentation format consists of the following:

• The Information Value Proposition
• Business Drivers for defining value
• Critical factors in placing financial value on information assets
• Case study: Transport Canada
• Tactical steps for defining and communicating the financial value of information assets

1:15 pm - 2:15 pm

Information Stewardship: From Vision to Implementation and Beyond

Become a data tour guide for information quality in your company. Learn how Anthem Blue Cross Blue Shield’s Southeast region took poorly organized Meta data and developed a formal information stewardship program. This presentation will show how to create, organize and manage Business Metadata, Data Quality, Training and Awareness, and Communications. Attendees will gain an understanding of roles and responsibilities, value added, success criteria and measurements, Meta data gathering tool kit, standards and guidelines, and more.

• Creating the program
• Organizing the program:
  - Data Gathering Tool Kit
  - Identifying Success Criteria and measurements
  - How to establish value added
• Managing:
  - Business Metadata Management
  - Discovery tools
  - Management Tools
• Training and Awareness:
  - Information Stewardship Website

A Contrarian View of the ODS Value in a CIF

Conventional wisdom on the role of operational data stores (ODS) in developing and managing a corporate information factory (CIF) has been a top down approach. The ODS has historically been an interim, staging area where CIF source data is staged and then transformed into a data warehouse or data mart. Nextel’s experience, however, suggests that the CIF’s value and future may lie in its ODS rather than its integrated data warehouse. This article advocates a bottom up approach, and challenges the conventional implementations. The Nextel experience is summarized in the following eight misconceptions:

• Operational Data Responsibility - The ODS can serve as a data replication point among operational systems.
• Linkage - The ODS allows functional analysts to translate strategic decisions into operational actions, measuring and monitoring impact.
• Archaeology - The ODS allows lost or incomplete business rules to be re-discovered from the behavior of source systems.
• Requirements - By sourcing more data than required, the ODS can isolate the CIF from requirements changes.
• Business Case - The ODS can justify the CIF with less discretionary and more persuasivebusiness cases.
• Risk- The ODS can convert the CIF’s data quality challenge from risk to service.
• Impact - The ODS can add smaller tactical impacts from operational reporting to the benefits of the CIF.
• Sponsorship - The ODS allows a CIF’s sponsorship to extend beyond an analytical champion.

Managing Your Project Manager: A Survival Guide for Data Professionals
Karen Lopez
Principal Consultant
InfoAdvisors, Inc.

As we are asked to do more with less, project pressures can lead to compromises, shortcuts, and other streamlining techniques. These shortcuts influence the quality and completeness of data management deliverables, yet most project managers have only a high-level understanding of what we do and what we require to do it. How will you respond when your project manager asks you how long it will take, how much will it cost, and how your efforts should be reflected in the project plan? This highly interactive (and sometimes irreverent) discussion will include:

• Warning Signs: When project pressures influence you ability deliver
• Getting It Right: Questions to ask when estimating data management activities
• Survival Tips: Making the best of more for less
• Resources: Where to turn for other survival tips

How to Implement a Quick, Low-Cost Metadata Management Program:

This presentation will show you how to leverage the work from other Federal
Agencies and save millions of dollars in metadata implementation.

• Getting Started is not hard.
• Communication is the key.
• Don't reinvent the wheel.
• Get group support through a user's group.
• Next Steps
• Benefits

Instituting the Meta Data LifeCycle
Barbara Nichols
Principal, Consultant
Metaview360, Inc.

Many different kinds of tools are used to create and maintain a data warehouse, such as: data modeling tools, data extraction, transformation and loading tools, data quality assessors, databases, gateways, business intelligence and reporting tools, web sites, and portals. Meta data occurs throughout the entire process, and with the use of each kind of tool. An effective meta data management lifecycle captures the meta data from all points in the process, organizes it for analysis, and makes it available to all the processes and people that need it. This presentation describes a life cycle for meta data management, and the corresponding kinds of tool implementation architectures that support it. The presenter has implemented this approach successfully at multiple client sites. The presentation will cover:

• The Life Cycle Components - It’s not an SDLC
• How Tools Enter the Mix - An Effective Tool Approach
• Dealing with Implementation Obstacles: Technical, Organizational, and Cultural

PANEL: Data Management: The Next Big Thing
Tony Shaw, Wilshire Conferences
Todd Stephens, BellSouth
John Friedrich, JRFII, Inc.
Charles Betz, Best Buy
Craig Mullins, BMC Software
Neil Raden, Hired Brains

At the past two conferences we've conducted the "Next Big Thing" panel and have correctly identified numerous significant trends in the data world, including the emergence of unstructured data management, privacy issues, compliance requirements (such as Sarbox) and the increasing pace of change and evolution in data roles. In our first panel we also predicted, quite notoriously, the end of traditional, centralized data management as we then knew it (we'll leave it to you to judge if we were correct on that one!). So will we be on target again in 2004? We'll try to keep the tone of the panel both informative and entertaining, certainly fast-paced, and most likely controversial. By the end of the discussion we expect to have some serious new ideas and directions for you to think about. As the conference draws nearer we will define the topics more specifically, but here is a quick sample of the topics we’ll be looking at:

• Major “macro” trends shaping data management, including financial cost reduction, outsourcing, security, real-time decision-making, customer-centricity, compliance, regulatory influences
• What new issues and technologies are coming that you will have to know something about? Artificial intelligence? Autonomics? Digital rights management? Identity management? More unstructured data? Process integration?
• What will your job entail 2 years from now? 5 years? 10 years? Will you even be working in the same field?
  

Optimizing the Value of Metadata for Business People
Hans Yeager
Partner
SH Group

If you ask a businessperson if metadata is important to them, he or she will more than likely say “no”. If, however, you ask them whether it is important to know how an element in a report was calculated, or to know how current the information is, or to know from where the information was obtained, you’ll likely get affirmative answers on all counts. This presentation will help you understand what is involved in delivering a practical business intelligence solution and covers the following five areas.

• Metadata that is important to business people
• Approaches to managing metadata
• Idea places to manage business metadata
• Business intelligence software metadata integration

Thursday, May 6, 2004
8:30 am - 9:30 am

Establishing Best Practices within American Century's Data Services Department
Kevin Phelps
Data Analyst - Specialist
American Century Investments, Inc.

After the Data Administration Team was established within the Data Services Department, the standards, processes, and work flows within the team all had to be evaluated and/or created in order for the existing DBA Team and the newly established DA Team to work effectively and efficiently together; as well as with the application areas. This presentation will cover the historical and on-going efforts to establish these “Best Practices” within our Data Services Team, including:

• Types of Data Models Defined
• Data Modeling Standards
• Education to application areas on Data Services
• Data Services Work Flow
• Data Services Engagement System
• XML Management
• Metadata Management
• Change Procedures to manage all these practices

Driving Strategic Direction and Results for Enterprise Data Architecture at Intel
Gregg Wyant
Chief Data Architect
Intel Corporation

The Chief Data Architect at Intel Corporation will discuss the challenges of introducing Data Architecture as a major management initiative in a large and distributed manufacturing company. The major challenge is to illustrate to senior management the strategic advantages of establishing an Enterprise Data Architecture, simplifying tools and methods, managing information with the same care as the company manages other valuable assets. He also showed his CIO level why central administration of data can actually free businesses users to develop more creative and useful local applications, and add greater data security. Mention will be made of the power of the Zachman framework to direct individual efforts, and Data Quality, as defined by Larry English, to locate systems of origin and records of reference that could serve the needs of the company with consistently defined business information. The last part of the session will be open to invite senior managers and those who are likewise involved in Enterprise Data Architecture to share their successes and warn us of traps that lie ahead.

• Establish Enterprise Data Architecture org and Chief Data Architect role
• Base Enterprise Architecture on Zachman Framework
• Mandate Common Tools and Governance Process across organization
• All data (and its associated metadata) aligned to the Enterprise Model
• Data security centrally administered; data access centrally controlled

Putting "Place" in the Database - Spatial Information Storage and Use
Paul Baynham
Senior Systems Analyst
PlanGraphics, Inc.

We are witnessing a movement of location-based information from proprietary software packages into enterprise databases. Geographic Information Systems (GIS) has been the domain of adepts with very specialized knowledge, and for the most part remains so for data creation. However, a massive increase in the amount of location-based information and the need to distribute and deploy it over a widely disbursed enterprise has led to databases that are storing location information in new and dynamic ways. The information about an object in a database can now include that object's location - from a minute bit of the human genome along the DNA double-helix to the multi-dimensional map of the universe to the mundane coordinate of the nearest pharmacy. This presentation will discuss the notion of location, how it might be defined when coming up against the very small and the very large, and the impact this may have on data modeling and management.

What Your Mother Never Told You about Meta Data
(Including, No One Makes Their Own Bootstraps!!)
Richard Weimar, Jr.
Senior Consultant
State of Michigan

We have just successfully completed the first phase of the meta-Data Repository for the State of Michigan’s welfare organization, The Family Independence Agency (FIA). We have progressed from being “green as gourd guts” to relatively sophisticated journeymen about what meta-data is, its true value and how to manage it to benefit the business. We were surprised by the significant potential value and power in good meta-data of broad scope which we had not considered initially. We are beginning to take advantage of these attributes. The key is - No one does this successfully by themselves. Other people have good ideas too! Accepting this up front and using it as the driving principle will significant contribute to a successful project.

• Doing it Right the First Time (for your organization), the Scope and Plan
• Getting the Business People involved From the Beginning
• Choose a meta-Data Management Tool Set That Fits Your Needs
• Dig ‘Till You Find the Correct meta-Data
• Use the Repository to Bring Data Standards to Your Organization.
• Make the Repository Painless to Use and Pretty (Pretty Counts!)

Refactoring Metadata: Finding Architectural Compatibility through Structural Comparisons
Baden Hughes
Research Associate
Department of Computer Science

A plethora of metadata standards are emerging, often founded in different descriptive traditions, and documenting an increasing variety of objects. As a consequence, there is an increasing need to be able to compare, merge or translate metadata between different standards. Prior to the conversion between different metadata standards, an interoperability analysis must first be undertaken to ensure that the correspondences between XML architectural components (namespaces, schemas, DTDs) and XML documents (elements, nodes) are understood and any incompatibilities resolved. Methods for such analysis are often complex, and require reference to formal standards in order to clarify structural relations. With the growth of metadata catalogues, there is increasing importance of automated methods for such large scale analysis and conversion tasks. In this paper we will first consider the influence of metadata heritage on structural analysis approaches and review some formal comparison methodologies. Next, we will investigate comparisons at both an XML architecture and XML instance levels. Finally we provide some abstracted but robust techniques for the automated analysis of metadata instances.

• Metadata Lineage/Heritage
• Comparison Metholodogies
• Architectural Comparisons
• Instance Comparisons
• Robust Techniques

The Return of the Data Warehouse: This Time It's for Real
Neil Raden
President
Hired Brains, Inc.

Despite the centralization of operational data, data that is needed for analytical processing must be extracted, transformed and loaded into a data warehouse before it can be used. This