• Bob Bickel, Founder, Bickel Advisory Service
• John Goodson, VP of Product Operations, DataDirect Technologies
• Dean Guida, CEO, Infragistics
• Geoff Brown, Technical Director, ATS Core Technologies, Oracle

Data Integration: Strategic and Business Perspectives

Katherine Hammer
President and CEO
Evolutionary Technologies

When Best Practices Aren't Good Enough
Katherine Hammer

One of the largest contributors to the general skepticism about technology is the failure to understand the complexity and importance of data integration management to every IT initiative. While there is a general understanding that data integration is important - to business intelligence, EAI, CRM, and so on - there is little attempt to treat data integration as an key factor in an effective enterprise architecture. One of the largest contributors to this failure is the process large organizations use to evaluate and purchase software, and this failure is a large part of why the cost of software ownership remains so high. This presentation analyzes these major problems with the way software evaluation is conducted and suggests how companies can use a few key criteria and a revised methodology to solve this problem.

• Application consolidation
• Cultural conflicts of interest
• Limitations of industry analysts
• Change management
• Risk management
  

Service-Oriented Integration and Process

Ron Schmelzer
Founder and Senior Analyst
ZapThink, LLC

Integration is not about simply plugging two systems or organizations into each other. The vision of "plug and play" application and system integration is a pipe dream that may be appropriate for in the distant future, but right now enterprises face the more immediate challenge of connecting arbitrary systems in a manner that is cost effective, manageable, efficient and secure. Ron Schmelzer, senior analyst, ZapThink, gives you soup-to-nuts expertise for Web services and the Service-Oriented Architecture (SOA), as they represent an approach for integrating systems using an abstracted methodology called Service-Oriented Integration (SOI). Discover how Web services is becoming a key element to simplify and enable integration between legacy, heterogeneous and disparate systems. Gain real-world advice on:

• The use of Web services for integration
• How EAI and B2B integration are merging and what this means to you
• Web services integration with mainframe and legacy applications
• How SOI technologies and approaches solve lingering integration issues
• Basic elements of SOI
• Drivers and motivators for SOI adoption
• Market segmentation
• Key vendors and technologies in the SOI space

A Little Appreciation - Is it too much to ask for?

Moderated by Graeme Simsion Panelists:
Graham Witt	Karen Lopez	Joe Maguire	Len Silverston

The burning issue for many modelers is to be relevant, needed and appreciated: it's a day-to-day issue in terms of winning arguments on approach and design at the project level, and a career issue in the sense of "is there a future for data modeling professionals?".

This panel looks at the practical issues facing the professional modeler (data or data and process) in today's world, and what this portends for the role of modelers in the future.

• How do you convince the stakeholders of the importance of modeling?
• How do you deal with disputes?
• What happens in an agile project / package implementation / outsourced development?
• What will be the keys to staying relevant and employed? How do the consultants do it? Are there secrets you can learn from?

Unstructured Data Management:
Concepts, Tools, Applications and Future Directions

The second part of the discussion will bring in 3 of the industry’s leading companies to talk about the tools that are currently available to manage unstructured data (including some demos), and where the technology will go next. This moderated discussion will explore the biggest challenges and opportunities in this nascent field, how to integrate unstructured sources with structured data, and where to look for the high-payoff applications.

• Definition and importance of unstructured data (i.e., text, video, audio, etc.; I'd mostly focus on text)
• Taxonomies and meta-tagging in managing unstructured data
• Typical applications and their requirements
• Technologies for text categorization and search/access
• Discussion and classification of major vendors

UML for Database Design

Terry Quatrani
UML Evangelist
IBM

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
• 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.

To Federate or Consolidate: 10 Things to Consider Regarding Data Integration

Ho-Chun Ho
President
HoTech Corp

Despite our best intentions, it is the reality in modern enterprises that different parts of an organization use different systems to gather, store, and deliver critical data. Only by combining the information from various systems can an organization realize the full value of these disparate data sources. There are many mechanisms to integrate data: data layer integration, data access layer integration, application-specific solutions, application-integration frameworks, workflow or business process integration frameworks, digital libraries with portal-style integration, search-engine-oriented integration, data warehousing, and database federation. When architecting data in support of any of these integration options data architects often face a tough decision-- we need to choose between consolidating data and federating data. This presentation will share the insight including technological issues, organizational impact, as well as cost factors. Among other considerations, this presentation will address:

• Basic principles and criteria for exceptions
• Data quality and integrity
• Transaction characteristics
• Performance, currency, and availability
• Abusive reuse of API's and middleware
• Structured, semi-structured and unstructured contents
• Ownership and turf wars
• Actionable meta-data

XML, Your Data, and You

Evan Levy
Senior Partner
Baseline Consulting Group

There's lots of buzz about XML as a data management enabler, but XML is no silver bullet. In this session, Evan Levy covers where XML fits with your data management, data warehouse, or data integration strategy. He navigates the benefits and pitfalls of using XML as a data management solution, including:

• Popular myths about XML
• XML for moving data
• XML for accessing data
• XML and ETL
• XML and XQuery
• Key job roles and XML

Evan will provide a checklist of the real-world challenges XML faces in corporate IT environments. He will discuss real-life case studies of XML in action at companies (a case study of a bank, and a case study of a communications company) which have succeeded in leveraging it for bona-fide business benefit.

Data Profiling Technology
How to Recover Metadata and More

Jack Olson
CTO
Evoke Software

Most IT projects depend on accurate and complete metadata for successful completion. However, this is rarely available. This presentation describes how the emerging hot technology, data profiling, is used to recover metadata from the data and provide other information such as information on data content and quality. Learn from Jack Olson - the person responsible for creating the data profiling space - about:

• How to extract attribute properties from data
• How to extract structural relationships from data
• How to formulate and validate data rules from data
• How to locate data quality accuracy problems in the data
• Why data profiling technology can deliver what other techniques cannot

Active Metadata

Adrienne Tannenbaum
President
Database Design Solutions

Organizing data across the enterprise has always been a challenge. Today we are also deciding whether or not to organize metadata across the enterprise. With so much metadata and so little time many metadata solution efforts involve an assessment of all existing metadata's accuracy and usefulness. When discrepancies are identified, subsequent metadata solutions are required not only to represent updated and accurate metadata, but also to ensure its livelihood. Active metadata is always up-to-date since it is not a copy or redundant version of that information required to identify, define, locate, source, and access the associated instance data. When all metadata is active, metadata solutions are always current and useful. In many scenarios "active metadata" is created automatically when we create whatever is being described. From that point forward the metadata is always as functional as it can be. Implementing a metadata solution within the boundaries of today's corporate information environment requires active metadata functionality. Adrienne Tannenbaum will explain the role a metadata solution should play in delivering and maintaining active metadata. She will contrast active vs. passive metadata connections, illustrate various "active" architectures, and discuss the ideal approach to developing an active metadata solution.

Name/Address Matching and Consolidation

David Raab
Partner
Raab Associates

Name and address matching has become a huge priority in recent years, in a wide variety of contexts, from CRM systems to fraud detection, and from data quality applications to identity profiling for homeland security. In this session, industry expert David Raab provides an overview of the issues and technologies in identity matching. He'll discuss the different challenges of US and foreign data, provide an introduction to the tools that are available in the market today, and offer tips on testing the alternatives.

• Overview of name/address matching process and issues
• Competing technical approaches with strengths and weaknesses
• Dealing with non-U.S. data
• Brief discussion & classification of major vendors
• Testing alternative systems

A Comparison of UML Class Models and ERDs for Data Modeling

Paul Dorsey
President
Dulcian, Inc.

It has been suggested that UML class models cannot be used for data modeling. Some recognize that it can be done but should not be done. UML class diagrams have not traditionally been used for data modeling but have mainly been used for object-oriented database design. This presentation will demonstrate how, with some natural extensions, UML class diagrams can be used very effectively to create a modeling environment that is superior to ERDs.

A number of extensions to UML class diagrams, including primary key specification, History and Audit keywords, display functions and derived attributes will be discussed. Specific examples where UML representations are clearer and more precise than their ERD counterparts will be shown.

Specific topics to be discussed in this presentation include:

• UML Advantages:
  - Aggregation and composition
  - Generalization
  - Cardinality
  - Stereotypes, constraints and keywords
  - Interfaces
  
• Extensions to support data modeling:
  - Data modeling
  - Logical primary keys
  - Audit
  - Display functions
  - Derived attributes
  - Domains (value list, validation)
  
• Examples:
  - Many-to-many
  - Reference tables
  - Cardinality
  - Use of Interfaces
  - Use of derived attributes
  - History and audit

Speaker Note: In 1998, I wrote what was probably the first book on using UML for data modeling. I recognize that using UML for data modeling is a very tough problem. But now that I exclusively model using UML, I must conclude that it really is better than ERDs. Of course, the factors that make it a better method are largely the extensions used to help the data modeling environment. Those same extensions could have been added to ERDs, but generalization, methods, aggregation, composition, and association relationships are all places where UML has a native advantage over ERDs.

Exploring the Converging Worlds of Data Integration Tools

Faisal Shah
Chief Technology Officer
Knightsbridge Solutions

ETL … EAI … Web services … Do these product categories even exist any more? They do right now, but Faisal Shah will explore the future of these tools and how organizations in need of data integration should change their thinking before selecting a specific tool or tool category. While the categories are experiencing convergence among features, he will also point out significant breakout features among select products that make them leaders in their category. Faisal will walk through features you should consider when making a data integration tool decision, and how and organization should evaluate their current and future feature needs and try to match the appropriate tool that will provide the best long-term investment.

• How data integration tool categories will evolve
• How to determine your organizational data integration tool needs
• How to select the appropriate integration tool
• How to ensure the best long-term integration tool decision

XML: A Component of Metadata and Enterprise Architecture

Ben Jenkins
Senior Architect
BellSouth

This session focuses on how the Extensible Markup Language (XML) applies to metadata, and offers an overview of one real-life implementation of an enterprise XML repository. Participants will learn the fundamental segments of XML architecture. As the universal language for data on the web, XML gives you the power to deliver unambiguous data meaning between business applications, search capabilities, and static/dynamic presentation. The Metadata Services Group within BellSouth has spent the last 4 years developing an Enterprise Metadata architecture solution which includes the pervasive role of XML. This conference will develop the attendees understanding of XML and how it has been used in a successful enterprise metadata implementation.

• The fundamentals of XML
• Applying the principles of XML to metadata
• What’s in it for metadata: RDF, Dublin Core
• Is XML all there is to an enterprise metadata architecture?
• A successful implementation of an enterprise XML repository

How to Build a Great Relationship with your Data using Profiling and Quality Assessment Techniques

Brad Darrach
Information Quality Analyst, IT Business Systems Support
Fallon Community Health Plan

The honeymoon is over; now you’re married to your data. Unfortunately, it may have been an arranged relationship and you didn’t have much time to get acquainted first. Here is a session in “speed-dating” to help you develop a strategy to get to know your data quickly and efficiently - before some hidden personality disorder ruins your life! There are some fundamentals that we will show you to help you reveal some of the mysteries in a hurry and empower you to decide what should happen next. Then, we will show you how to monitor your relationship and watch for signs of trouble and keep you out of counseling. Brad will share his successes and challenges to help you target your next project for success. He will discuss:

• Metadata issues – critical for integrating data
• Defining data quality – establishing appropriate metrics
• Conversion testing vs. ongoing maintenance
• How to let your database work for you – sample queries and scripts
• Empowering your customers to help

Active Metadata
Discussion and Vendor Roundtable

Andrew Manby
Director of Platform Product Management
Ascential Software

Greg Blumstein
President
Data Advantage Group

Naresh Govindaraj
Senior Product Manager for Metadata and Interoperability
Informatica

Adrienne Tannenbaum's presentation will be followed by an interactive vendor panel. Invited metadata solution vendors will discuss their products within an "active metadata" limelight. Attendees will then be given an opportunity to present specific questions to one or more vendors. Adrienne will serve as the mediator of this interactive discussion.

New Directions in Record Matching and Relationship Linkage

David Raab, Raab Associates (moderator)

Frank Dravis, Vice President Information Quality, FirstLogic, Inc.

Ramesh Menon, VP, North America, Search Software America

Andrew Borthwick, President & CEO, ChoiceMaker Technologies, Inc.

The "Know Your Customer" movement is driving business strategies that need "total customer knowledge" or the "360 degree view". From an IT perspective, identifying the relationships between customers, contacts, organizations, consumers, households etc. across multiple systems and databases becomes a basic requirement of today's systems. And if you’ve been involved in systems or projects that need to integrate or merge such entities, you’ll know that it’s not enough to perform a simple string comparison of two records to find a relationship or a duplicate. This will uncover exact matches only.

There a lots of products on the market that enable relationship discovery, matching and linking. In this moderated discussion we’ll talk to three of the most prominent companies in the field to learn what the state of the art (or science) is in terms of the technological capabilities of products, and what they see their customers doing in terms of best practices, methods and processes.

• Is a single strategy for finding matches enough? How do you know what you’re missing?
• What’s the downside/upside to using multiple matching programs?
• Discovery processes
• To merge/purge or “link”
• The problem of approximate matching, and strategies to deal with it.
• Strategies to measure and maximize quality
• Measuring record linkage and deduplication accuracy
• Methodologies for determining the extent of record duplication within a database
• Measuring the accuracy of a record matching solution, including false matches

Integrating Data with Processes: Data Model-Driven Applications using CASE

Jose Borja
Senior Analyst Programmer
Mayo Foundation

Are you tired of developing detailed data models that end up collecting dust after technical design and are never used again? Then join me and learn about data model driven applications and the CASE tools that make it possible to permanently glue your data model into the processes and procedures that make up an application.

Witness proof of the importance to use tools that include the data model in the application and learn how CASE tool environments have a leg up in providing automated solutions to enterprise data integration issues, database management procedures, and impact analysis procedures.

The session uses live demonstrations of an CASE generated Client/Server application to cover these topics:

• CASE environment and the Encyclopedia concept
• Data Model development in an CASE environment
• Marrying the Data Model into the processes that implement the business rules
• Logical to Physical model transformation
• Impact Analysis (change Management)
• Managing denormalization in CASE. Implementing a data model change, modifying the processes, and regenerating the application in minutes not days!

Speaker Comment: I will present in a vendor neutral environment how CASE tools help solve issues on enterprise data integration, data and process management, modeling, and model contents analysis. I believe participants will love seeing how their Data Models can become a live part of their applications and not just an analysis phase deliverable and database schema for DDL.

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.

Data reusability is the process of collecting, managing and storing electronic data in all forms and formats to promote the efficient use of that data between business units and applications while minimizing data redundancy. It is more specific than data sharing, in that data sharing can involve data duplication, while the goal of data reusability is to eliminate unnecessary duplication. It is more specific than data integration, in that data integration is the melding of information from disparate systems, while the goal of data reusability is to integrate while optimizing and standardizing the common data.

The presentation discusses a generic ECDA based upon the New Jersey Common Data Architecture being deployed by the Office of Information Technology:

• 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

Enterprise Information Integration (EII)
Emerging real-time solutions, standards and tools (including an introduction to XQuery)

Nitin Mangtani
Technical Program Manager
BEA Systems Inc

Information is locked in the islands of relational databases, EIS systems and proprietary applications. The need to integrate information in real-time has greatly increased with the advent of web and more focus on self-service based applications. This session talks about information integration challenge in building self-service portals, composite web services and business processes. We will look at traditional solutions of information integration such as ETL, EAI, custom coding and their pros and cons. Then we will talk about emerging solution called Enterprise Information Integration (EII). This discussion will cover basics of emerging W3C standard XQuery and the need for native query language for XML. We will discuss how developers can use XQuery to create reusable views of enterprise information. Finally we end this session by covering a real world example of applying XQuery to deliver rapid information integration solution.

• Information Integration challenge
• Business requires aggregated access to real time information
• Data Sources are heterogeneous
• Traditional information integration solutions – ETL, EAI and custom coding
• What is EII?
• XQuery Basics
• Real world example and solution using EII technology

Enterprise Data Maturity

Burton Parker
Principal
Paladin Integration Engineering

Peter Aiken
Founding Principal
Institute for Data Research/VCU

This presentation will summarize results of research into the state of data management maturity in 200+ large commercial and non-profit organizations, and government agencies. The presentation will include a brief review of the Enterprise Data Management Framework that underpins the research efforts. The Framework consists of a Template for Enterprise Data Management, including roles and responsibilities, and a Template for Enterprise Data Management Maturity. Profiles of the research results into the state of data management maturity will be summarized in a number of matrixes based upon the Templates of the Enterprise Data Management Framework. The presentation will also include summaries of specific commonly found findings as reported in a number of data management process improvement engagements. Attendees at this presentation will understand:

• The elements of enterprise data management maturity.
• The results of Virginia Commonwealth University’s research results on enterprise data management maturity.
• Summaries of selected enterprise data management maturity evaluations.
• Specific comments commonly heard from participants in enterprise data management maturity evaluations.
  

Semantics in Business Systems

Dave McComb
President
Semantic Arts

Long marginalized, Semantics is emerging as the trump card in application development and integration projects. Getting ready to normalize your data model? How do you know you’re normalizing the right data? Getting ready to integrate two systems? How do you know what the data definitions really mean?
Whether addressed early or late in a project, the meaning of the information will eventually assert itself and need to be dealt with. This presentation is an introduction to Semantics and its application to business systems. It will be a cook’s tour of how Semantics permeates these areas of development:

• Conceptual Design and Semantic Modeling
• XML and the definition of meaningful schema
• Business Rules and the advantages of basing them on an semantically rich ontology
• Ontologies: what are they anyway?
• Systems Integration and Semantic Brokers
• The Semantic Web

Quantifying the Operational and Financial Risks in Enterprise Data Architectures

Chito Jovellanos
President & CEO
forward look, inc.

How did the banking industry formally assign "economic value" to its data? The banking sector has recently adopted a new approach to measuring the contribution of operational data and systems to the fiscal health and performance of financial institutions at-large. The "Basel II Accord" is a major update to regulatory capital requirements that incorporates dramatic new provisions for quantifying the broad operational risks which financial institutions encounter.

This presentation highlights the evolution and deployment of the Basel II Accord, with particular attention to the business-critical data and systems that these technology driven firms rely on. More importantly, this session offers insights and techniques that will enable data architects and information systems managers from a broad spectrum of industries to:

• Use simple methods to identify and measure the potential risks and financial liabilities inherent in a company's data architecture and supporting systems
• Communicate effectively about data management and operational risks in terms that a CFO can appreciate and use
• Apply these methods to other initiatives such as BCP (Business Continuity Planning) and DRM (Disaster Recovery and Management).

A worksheet highlighting the application of the techniques discussed in this session will also be presented.

Data Modeling: A Developer's View

Roland Berg
Principal Consultant
ThinkSpark

How often have you created an elegant model only to find out that the developers couldn't understand how to use it? The initial thought is frequently “What’s wrong with the developer? This is simple!” Unfortunately the problem isn’t always the developer. Our experience has shown that the problem is often related to inadequate documentation and/or communication of what the structures really represent.

This presentation looks at data modeling from the developer's perspective exposing the data modeler and architect to the issues and concerns of the developer. It provides guidelines for modelers and architects to help them communicate appropriate information to the development team so that they may design and write their code as efficiently and effectively as possible. The approach presented involves training and coaching strategies as well as identifying an appropriate type of documentation for the other members of the team.

Once the developers have an appropriate level of information they frequently find enjoyment in using the structures we have defined. The result is a better and more effective working relationship between the modeler-architect and the designer-developer.

Supporting Multiple Views of Enterprise Information
(or...Get Out of My Life, but first could you drive me and Cheryl to the mall?)

Martin Dunn
Vice President
Alliance Consulting

You may not need teenage children to relate to this humorous book title. If you have ever undertaken an enterprise integration project, you may share a similar relationship with your application owners.

In the politically charged waters of enterprise integration, it is often necessary to support multiple views of reality. Creating a "single view of ..." has become a familiar mantra of integration technology vendors. By definition, there can be only one "single version of the truth" but recognizing, understanding, managing and supporting differences of opinion is a key aspect of any integration project.

In this presentation we discuss data management techniques and processes that arise from supporting multiple views of enterprise information. We will review some successful techniques developed to cater for this difference of opinion and discuss the implications of these solutions.

XML Vs. Relational - The Top Ten Differences

Jim Stewart
Director of Consulting
ASIX, Inc.

This presentation explains the fundamentals that differentiate XML and Relational technology. Although the differences between XML and relational seem obvious, the problem of selecting the right one it is not that simple when you take a closer look. Reading articles and attending seminars shows that even the industry “experts” have basic misunderstandings. Arguments for and against the use of the two approaches show confusion about the best uses for each, how they are different or similar, and apparently conflicting claims in several areas. The advent of XML DBMSs makes the issue even more confusing.

This presentation clearly identifies the top differences (and similarities) between the two technologies in a way that will help data professionals understand them, select the correct solution for an application and make sound architectural decisions on their use.

The Top Ten “differences” that will be reviewed are:

• Primary Purpose
• Data Paradigm
• Metadata Approach
• Ease of Understanding
• Relationships
• Object Identification and Navigation
• Query Ability
• Flexibility
• Data Integrity
• Performance.

The Structural Integrity of Source Data

Joseph Novella
President
Anthem Consulting, LLC

Many data profiling and assessment efforts tend to focus on domain studies tasks and techniques. However, understanding the content and scope of individual columns and fields is only the first step in developing a complete data assessment. This session introduces techniques used to evaluate the structural integrity of source data.

• Functional dependencies
• Evaluation techniques
• Normalizing non-relational data
• Effective sampling techniques
• Data quality error or embedded table?
• Products on the market

Positioning Metadata as a Business Asset
(and get funding for your project)

Daniel Riehle
Principal
GetReals Inc.

Metadata is seen as a technical necessity, not as a business asset. This is a strategic error on the part of IT organizations. The reality is that funding for Metadata will never be significant if you can not morph metadata into a enterprise-wide business asset. This presentation shows how to use an extensible repository, COM objects, XML and ASP to generate self-guidance of business people through the mountains of technical metadata inherent in your IT organization. As an example of the technique, the presentation relies on the need to reflect “Lineage”, the journey that business-valued information takes from first source (Legacy systems) through final targets (BI Tools).

To properly position metadata as a business asset (and hence secure funding for the IT effort), you must make the requisite detailed metadata transparent to the business user yet keep these users’ need foremost in the overall architecture of the enterprise metadata. It is a sneaky detail that by focusing on the business value of metadata, you accumulate the technical metadata required to streamline the activities of IT.

The underlying technology of this presentation is Teradata’s Metadata Services but the concepts and techniques are universally applicable to any extensible repository engine. Key take-away points are:

• Extending the repository to reflect business needs
• Data acquisition and parsing of metadata sources (lineage and transform acquisition)
• Summarization of lineage
• Applicability to other enterprise metadata tasks
• Business and technical funding points (budgeting).

A Strategic Reference and Master Data Framework for Enterprise Information Delivery

Kapil Khanduja
Practice Director, Data Management
Data Foundations

Problems of information disparity have plagued the IT industry since its beginning: The inability to integrate data across business units, inconsistent business definitions in the organization, the inflexibility of applications to respond quickly and cost-effectively to business changes; all these problems result in incomplete and/or inaccurate business reporting.

Current solutions include point-to-point mapping, transformation, cleansing, build/buy integrated transactional systems and custom applications to centralize the maintenance of master files. But the “strategic” approach to this problem involves the creation of a foundational enterprise information layer for the business – a visible shareable reference data layer –that enables an “information-aware” organization.

Certainly some challenges exist in terms of getting consistent definitions, identifying business ownership, change management, transitions; regional standards, and deployment throughout the organization. But overcoming the challenges is possible using a methodological roadmap, and using tools to assist the transition and implementation; standards and process changes.

The presentation will be of interest to attendees involved in enterprise information delivery, data models, architecture, metadata, ETL, data deployment and reference/master data management.

Role Transformation: Data Analyst and Architect

Jane Carbone
Partner
infomajic, llc

Should the work of data analysts and architects remain forever separate, and if so, how can we ensure they communicate to best serve the enterprise today? This presentation looks at data integration from the organizational perspective and proposes some changes. The speaker evaluates the traditional roles of data analyst and architect and describes why change is necessary. It discusses how to effect change by proposing new model role descriptions. The presentation identifies gaps in current skills and knowledge and suggests how to address them. Finally, it evaluates organization structures that facilitate change.

- Traditional roles and where they break down
- Defining new roles
- Identifying gaps in skills and knowledge
- Overcoming gaps and barriers
- Positioning roles in the organization structure

Speaker Comment: We get lots of questions on people issues, and believe change needs to be addressed here as well as in technology.

Why Data Marts Proliferate: Business Semantics and Data Integration in Conflict

Robert Klopp
Director
Skyland Technologies

In most Business Intelligence implementations, data marts proliferate, creating a data management headache. Often this proliferation occurs despite the availability of a comprehensive, integrated, data warehouse.

In this session the author will describe modern data warehouse architecture, with dependent data marts, in terms of business semantics. The differing semantics inherent in operational, warehouse, and mart schemas will be introduced; data integration costs will be described in terms of semantic transformations; the costs will expose a flaw in current data warehouse architecture; and the proliferation of data marts will be explained as the result of that flaw. Finally, the application of federated database technology to the problem of data mart management will suggested as a way out.

The Role and ROI of Enterprise Schema Management

Jeff Dirks
CEO
Schemalogic

Enterprise Schema Management is a new concept driven by the need to improve information sharing, cut costs and increase responsiveness to changing requirements. Involving repository technology and a highly collaborative process, success requires leadership from the IT and business architects who establish best practices. With increasing usage of XML Schema, now is the time to treat schemas as an enterprise asset to encourage re-use and ensure interoperability.

In this session we will review the role and ROI of Enterprise Schema Management to help attendees understand, rank and financially justify this critical aspect of information integration. Attendees will learn the key aspects of Enterprise Schema Management, which include creating an enterprise schema repository, remote collaboration, balancing corporate standards with a natural diversity of viewpoints, change management, schema search and synchronization processes.

Based on real-world case-studies describing information integration within manufacturing, financial services and media companies, this presentation will describe best practices including the leadership, politics and process challenges that can impact success even more than any given technology. Most importantly, attendees will understand the key factors that produce business value and return-on-investment from Enterprise Schema Management

Attendees will leave this session knowing:

• How does Enterprise Schema Management enable reuse of XML Schema?
• Are enterprise-wide, cross-application schema standards possible?
• The downside of freedom: chaos as XML developers create arbitrary schemas
• How have pioneers managed the politics and process of schema stewardship
• Why management cares: financial benefits and ROI

Speaker Comment: Analysts and press are starting to write about how the proliferation of "arbitary" XML Schema is getting out of control. At recent conferences a number of people have come looking for a way to manage schema in general (gather, reconcile, search,...) and often triggered by the explosion of XML Schema.

Data Quality Assessment & Measurement:
Developing Data Quality Process Measures

Shaun Williams
Data Integrity Manager
H-E-B Grocery Company

Joan Brooks
EDI/Data Integrity Program Owner
H-E-B Grocery Company

Ranked by Forbes Magazine as the 9th largest private employer, H-E-B Grocery Company has over 300 retail outlets in Texas and Mexico, 55,000 employees, and close to 10 billion dollars in annual revenues. H-E-B’s systems process utilizes hundreds of information systems, many of which are legacy systems existing on antiquated platforms with little or no “on-line” data quality checks (edits).

In 2001, the senior leadership team at H-E-B formed the Data Integrity Group with these primary objectives:

1. Assess the data quality issues in H-E-B’s information systems, cleanse data issues, and help position the company for migration to more “modern day” applications.
2. Design and integrate data integrity as a way of life at H-E-B, through the use of data stewardship principles including process reviews, training, and measurements.

The Data Integrity department has spent the last 1½ years assessing and cleansing data that will be integrated with key Merchandising and Supply Chain applications. In addition, the group has developed a methodology, process, and technology for tracking data quality exceptions within a given process, and assigning cost metrics to these exceptions.

This presentation will discuss the processes, methodologies, tools and measurements implemented by H-E-B’s Data Integrity department in order to improve and sustain data quality, by discussion of the following topics:

• Definition of a process from a data quality perspective
• Identifying critical data within a process
• Engaging the business
• Defining and selecting the process measures
• Establishing costs and goals
• Tools and technology for measurement and monitoring
• Resolving data quality issues
• Embedding data quality into the project management process
• Implementing data stewardship and designing data quality into business processes, job descriptions, and training

Metadata-Driven On-demand Data Integration

Patricia Klauer
CEO
Eclipse Data Systems, Inc.

Dina Bitton
Chief Technical Officer
,Xtegra Corporation

Businesses, like cities, grow organically. Streets are added in response to growth, rather than planning, in the same manner that businesses add databases and applications. For the most part, growth is unmanaged until reaching a certain critical mass. At that point, it becomes obvious that additional growth requires infrastructure management. To successfully manage infrastructure growth, one must not only plan for the future, but also integrate the past.

Growing businesses have the advantage over cities in that hardware and software is easier to manipulate than streets and bridges. But even then, it is a non-trivial problem, given that we are still surrounded by decades of legacy data and systems. We will describe a metadata-driven data integration infrastructure that helps to preserve the legacy code, while allowing the organization to move forward with new uses for the data. This approach not only solves present problems of data integration such as data migration and data mart proliferation, but also provides a platform for future growth and changing business requirements.

The authors will address key issues such as:

• Persistently maintained data location and identification
• Standardized conceptual schemas
• Data transformation
• Preservation of local ownership and access controls

Speaker Comments: This is not a conceptual solution. This presentation describes new technology that is now available to support metadata driven real-time data integration.

Scientific Data - Challenges and Solutions

Olga Brazhnik
Chief Database Architect
Synchronous Knowledge, Inc.

Modern life profoundly relies on scientific knowledge and technologies build upon it. Scientific knowledge is acquired through the collecting and the complex processing of enormous amount of data, often measuring in terabytes or even petabytes. What is the process of extracting reliable knowledge from such an abundance of data? What are the challenges in the world of scientific data management?

Business and scientific databases are siblings but far from being twins; they face quite distinct challenges and develop divergent solutions, which they may share, albeit with some caution. In science, for example, there are significantly different ‘business rules’ depending on which scale applies, e.g. the result of mixing two chemicals cannot be calculated via simple algebra: distinct outcomes arise from different reaction conditions.

The presentation will cover data modeling, data processing, and data integration in science, emphasizing the complementary scientific solutions not found in the realm of business data. It will involve real life examples from the domain of bio-medical informatics, where the need for interdisciplinary data integration is the most pressing. This will be a lively, thought-provoking presentation and discussion of concepts that are new for business databases. Come with an open mind and learn about new challenges for database professionals in the realm of scientific data management.

• Complexity of scientific data
• Differences in processes of collecting and processing data in science and business
• The goal and promise of data integration
• Meta-data standards in life sciences
• The use and limits of applicability of UML, object-oriented databases, XML
• Open source development

Enterprise Semantic Models: Buy, Borrow, or Build?

Eli Israel
Lead Modeler
Semantic World

What makes a good Semantic Model? How can I make use of resources that I already have? What are some best practices?

This session will describe an introduction to semantic models and the roles they can play in an enterprise. It presents the qualities that identify a good model and the organizational factors affecting a model's adoption. It then asks if available models from a specific industry or organization are suitable for the specific business task at hand.

Additional questions that will be answered include:

• Which industries already have mature semantic models?
• What types of organizations are best suited to adopting such models?
• Which team members should be part of a model adoption team?
• What is a realistic project plan for integrating such models into the business?

The relative strengths and weaknesses of using relational models, object models, and XML Schemas for this purpose will also be discussed. Finally, real-world examples of best and worst practices garnered from modeling and consulting experience with Fortune 100 companies will be demonstrated.

Lessons Learned from Delivering Real-time Marketing Dialogs into Existing Operational Environments

Kevin Cavanaugh
VP 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 and 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.

• Extended customer data model requirements to support cross-channel dialog marketing.
• Architecture, system design and data integration strategies to support both synchronous and asynchronous real-time marketing application demands
• Techniques for integrating coordinating real-time, scheduled event triggered marketing dialogs across touchpoints
• Important lessons from recent deployments of real-time marketing in high-volume production environments.
• Guidelines for establishing and prioritizing cross-channel dialogue based on business value metrics and implementation readiness/complexity.

Standards-Based XML Management - an Insurance Case Study

Senthil M. Kumar
Director, Product Management
Analytic Software and Decision-making Tools
Fair Isaac Corporation

Insurance carriers spend millions of dollars each year processing policy applications and claims submitted by brokers and agents. This document-centric business is ideally placed to exploit XML, for which the ACORD standard has been defined for the exchange of policy information across the insurance supply-chain. ACORD addresses the challenge of standardizing extensions to documents to accomodate rapid changes in business.

This session will focus on how an insurance carrier manages their XML documents with automated validation yet allowing for rapid development of extensions to their XML schemas, taking advantage of web services, business rules and predictive modeling.

How to Uncover the Truth behind your Data
(and deliver $30 million in benefits by rectifying data errors)

John Longley
Data Cleansing Manager
Ministry of Defence

Paul Nettle
Data Cleansing Manager
Ministry of Defence

September 2000. The challenge: Integrate inventory data for millions of line items held across the UK Armed Forces. The problem: No one knows how good (or bad) the data is. The solution: Create a dedicated team to tackle the issue. Thus The Cleansing Project (TCP) was born, a small team working within the UK Ministry of Defence (MoD), that has delivered in excess of $30M of benefits from identifying and rectifying data errors. Starting with nothing more than determination and a pot of money in September 2000, TCP has become centre of expertise on data quality within UK government. The team are now a key enabler for e-business initiatives and EAI within the MoD, and an enabler for collaborative working within the UK defense sector. This presentation will describe how any enterprise can reap similar rewards by adopting the TCP approach.

• How to establish such a team and why the selection of its members is so important to success
• How to find and secure help from within the business
• How to select the right data profiling tools for the job and use them to best effect
• How to get data errors rectified and monitor data quality
• How to overcome the culture and other barriers that impede progress

Experiences with Meta-Data Management Across Tool Types

Christine Mandracchia
Manager - Data Administration
American ReInsurance Company

Effective meta-data management continues to be an undertaking requiring balance between the involved organizational roles and processes, and the capabilities of the specific tools available. In this presentation, Christine will describe certain characteristics of the meta-data environment in the organization prior to the acquisition of ETL, meta-data hub, and Business Intelligence products. She will discuss the subset of meta-data requirements to be supported for the business community, particularly the business names and definitions for the data warehouse contents. She will describe the "round trip" of meta-data from the data modeling tool, through a meta-data hub, to the ETL tool, and to the Business Intelligence reporting tool, and back.

The focus of the presentation will be on the issues that needed to be resolved in order to effectively execute this "round trip". These issues include which organization "owns" which type of meta-data, which tool is the "master" keeper of each type of meta-data, and how and when will the meta-data be moved among the tools under the various day-to-day situations of warehouse additions, updates, and deletions.

Open Source Data Warehousing and Databases

John Poole
Distinguished Software Engineer
Hyperion Solutions Corporation

The Open Source revolution is rapidly transforming the software industry in terms of both development practices and business models. Once regarded exclusively as the realm of software hobbyists, Open Source has become the software model of choice for many organizations. Data Warehousing and business intelligence (DW/BI) can benefit greatly from Open Source technologies, which enable both the construction of robust IT infrastructures, as well as an emerging class of software solutions for DW/BI, advanced analytics, and business performance management. This session provides a comprehensive overview of the Open Source contribution to DW/BI. Participants will learn why Open Source solutions enhance long-term, return-on-investment (ROI) of DW/BI projects, and provide corporate stakeholders with greater control over the maintenance and integration of their DW/BI solutions. An example case study in the use of Open Source technologies to implement a data warehouse is also presented.

• Overview of Open Source
• How key DW/BI concepts are addressed by Open Source solutions
• Case study of a DW/BI solution based on Open Source technologies
• Open Source support for platform, application, and Web services standards
• Open Source support for open integration standards: OMG MDA, UML, CWM, meta data patterns, and popular repository and data models

Modeling Business Rules

David Hay
President
Essential Strategies, Inc.

Other than terms, facts, and certain constraints, data models are limited in their ability to portray business rule constraints. Indeed, the more generalized a model becomes, the less it is able to show the business rules that constrain the domain being modeled. Where the topic of the model is itself rules, however (as in regulatory agencies), then the rules themselves can be modeled. In addition to showing the basic limitations of modeling to show constraints, this presentation will describe ways in which rules can be modeled, and will show examples in areas such a issuing permits, passing legislation, and so forth.

Corporate Compliance and Governance
Will New Legislation be the Killer App to an IT Recovery?

Karen Lopez
Principal Consultant
InfoAdvisors, Inc.

Who’d have imagined, a few years back, that IT would become a government-regulated environment? But now we have Sarbanes-Oxley and the USA Patriot Act and the Basel II Accord – to name just a few of the new laws that are encroaching on IT. Consider privacy regulation alone – there are over 220 bills covering information privacy pending in the US Congress as of July 2003. Throw in the new “don’t call me” list, European (and California) data protection, Gramm-Leach-Bliley, HIPAA, etc, and IT's role in corporate governance has forever changed.

It’s the ultimate good news/bad news story for data management. The good news is that we’re at the center of this new activity. The bad news is that we’re at the center of this new activity. It’s truly a double edged sword – and we don’t yet know which edge is sharper. But we had better handle things well, because the senior executives at our organizations are in most cases, either financially culpable or criminally liable, or both.

Lets start with the big picture on what all this new compliance requirements really means to data managers and how you can do your part to help your company meet its obligations.

Service Based Architectures - Defining the Issues for Data Professionals

Robert Abate
Principal Partner & CTO
Intellisys, Inc.

Ruben Tungol
Senior Architect
Novell Corporation

The Service Based Architecture [SBA] is the latest in unifying designs which, using industry standards and best practices, allows for complete business process and application integration. It documents corporate data, fosters the fast and real-time integration of legacy applications while providing for foundation for the future development of object based, n-tiered systems. This architecture was designed to allow for the replacement of legacy systems by removing pieces of legacy functionality while allowing for the simultaneous usage of both the legacy system and new applications.

We will review the development of the SBA, the technology terms used in this architecture, the foundation components, review the object-based Common Data Models [CDM] and data cleansing/integration issues, uncover the SBA components, explain how to phase in real-time messaging and show the follow-on benefits derived from the SBA.

SBA and its foundation architecture:

• Development of the SBA architecture
• Lessons learned from a number of different implementations
• Review best-practices of SBA implementations
• Demonstrate the benefits of it's implementation
• Debate implementation issues such as: Standards (J2EE, SOAP), Web Services, etc.
• Examples of fast implementations of batch (non-real time transfers) and the slower setup of messaging (real-time).

SBA Architecture components:

• Layered (integration services, runtime management services, metadata services and security services)
• Multi-faceted (includes development, testing and run-time environments, provides for completely scalable features and administration / monitoring of events)
• Industry Standards ((J2EE, Corba, SOAP, XML) Best Practices in SBA implementations (OO Development, architecture centric, model driven, iterative and component oriented)

Implementing an Integrated Enterprise-Wide Database

Ulka Rodgers
President
eTransitions, Inc

Andrew George
Director, Application Development
Corporation Service Company

Many corporations have talked about implementing an integrated database for their enterprise applications. This presentation is about what happened in reality. The presenters will discuss some of the challenges of managing multiple development teams, data conversion of critical data such as customers from multiple legacy systems, and the kinds of hard management decisions posed along the way. Using examples of applications, we will discuss:

• Data and code integration issues
• How the database played a central role
• How the organization and projects were structured to address the challenges
• Practical suggestions on what works and what does not for attendees embarking on similar integration projects.

Best Practices in Business Intelligence for ERP & CRM Suites

Aaron Zornes
Senior VP, Enterprise Analytics
META Group

The wholesale “information supply chain” change-out of information feeder systems that occurs with enterprise resource planning (ERP) deployments is an opportunity to vastly improve an enterprises’ analytic capabilities and concurrently reduce shadow IT costs. Enterprises remain challenged by their ERP investments’ ability to access and analyze enterprise information for business decision making. Concurrently, Oracle, PeopleSoft, and SAP are focusing on the analytic applications market and challenging best-of-breed analytics vendors such as Business Objects and Cognos. Un-architected “BI for ERP solutions” remain a huge shadow IT cost yet prescient BI projects stand to offer “break away” competitive advantage.

• Assessing the BI capabilities of mega application package vendors data warehouse offerings, e.g., Oracle OBIS, PeopleSoft EPM, and SAP BW
• Applying the right mix of best-of-breed analytics to maximize the ROI of ERP and CRM investments
• Superseding vendor-centric analytics via an enterprise-wide BI infrastructure strategy

Federal Enterprise Architecture: The Business Process Models

Michael Lang
Founder & EVP of Development
MetaMatrix

The Federal Enterprise Architecture (FEA) is a business-based framework constructed as a collection of interrelated "reference models" that will facilitate cross-agency analysis, and the identification of duplicative investments, gaps, and opportunities for collaboration among Federal agencies. The Reference Models act as a Target Architecture for which each agency will align. OMB and agencies will use the FEA for describing and analyzing information technology (IT) and other capital investments, and to improve Federal government service to the citizen. It includes a strong focus on delivering services to the citizen along with government- to- government process and information exchanges along with consolidating and integrating the services along lines of business.

In this presentation Michael Lang will present the theory brought forth in the Data Reference Model as well as discuss the enterprise architecture vision of the Business Reference Model. The Business Reference Model serves as the foundation for the other reference models - the Data Reference Model, Performance Reference Model, Application-Capabilities Reference Model, and the Technical Reference Model. The Information and Data Reference Model (DRM) is an approach and a Federated Information Model that can be populated along government Business Lines and be used across Federal, State, Local and International e-government initiatives. The approach is based on both sound information and data base theory, a serious need, and an approach that correlates with standards organizations to create an open and extendable family of information models. These models can be one element of each organization's push for information integration and increased consistency, commonality, and visibility.

This presentation will cover how government agencies are using data management, metadata management, Model-Driven Architectures, Real-Time Enterprise approaches, Service Oriented Architecture, Web services, information integration, and process integration.

Entities, Objects, and XML Schemas in One Model--Are You Crazy?

Richard Hecht
President
DATA Architects Technicians Analysts, Inc.

Is it possible that using different approaches in one modeling method can result in documenting and communicating data better than any one of these approaches by itself? This presentation explores a modeling methodology that combines the best of multiple approaches and furthermore maps the logical data to real physical implementations. This is not textbook and theory. This is actual practice and reality that arose from a need to help business users and developers better understand data and how it is implemented.

Specifically, this presentation addresses:

• Graphical techniques to display model information
• Approaches to present models to developers and users
• Concrete examples from real development projects

The examples show how the synergism created from this novel approach helps produce schematics that improve the documentation and communication of enterprise data and its physical implementations. This presentation is not for the purist who religiously follows the one-method-can-fit-all-no-matter-what theory. This presentation is for those who are interested in new concepts and creative techniques. Applying these concepts and techniques can help produce meaningful and useful information to answer the questions developers and business users have about data and proves that combining multiple approaches may not be as crazy as it first appears.

Speaker Comment: This presentation may very likely be controversial as many data people are self-described “evangelists” for one modeling method or another. Some seem to border on religious fanaticism, so the very idea of combining multiple methods may ignite sparks. However, if our profession is going to progress, new concepts and creative techniques need to be explored, and conferences and forums like this one are ideal to present these new ideas. At the very least they can provide fuel for debate and cause people who are in a rut to possibly rethink and refresh.

Meeting the Requirements for Sarbanes Oxley
Understanding the Business Semantics and Data Quality Issues for Compliance

David Steinberg
Solution Director
Idea Integration

Peter Vink
Business Development Manager
Idea Integration

David Kotler
Dechert LLP

For many in the Business Intelligence community, there is a comprehensive understanding of the data; we understand from a technology perspective what infrastructures work and recognize that how the data is captured and purveyed will greatly impact data quality. In many cases we understand where the shortfalls are in our processes.

This presentation will take a look at the data requirements of Sarbanes Oxley and other recent regulatory rulings. In addition to exploring the ramifications of data quality and business semantics in light of this regulation, technology framework, approach alternatives and rationale for initiating these efforts will be discussed. Profiles of organizations that should be concerned with compliance will be highlighted.

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
• Technology framework to meet functionality
• Profiles of organizations that should be compliant

Deriving a Data Model for Service Architectures

Peter Aiken
Founding Principal
Institute for Data Research/VCU

A metadata-based understanding is gained by a development process that applies eight transformations - organized into two phases - to each enterprise architecture/legacy system component. The eight transformations are applied in order to when effectively and efficiently developing an architectural component that is capable of delivering architectural and business engineering value. The transformations are illustrated. Transformations and other forms of data analysis occur using model refinement and validation (MR/V) sessions in conjunction with key subject matter expertise (SME).

Supporting Corporate Data Integration Projects

Melvin Jones
ETL Architect and Project Lead
T. Rowe Price Investment Technologies

This presentation will explore services, processes and procedures necessary to successfully support data integration projects operating in a shared environment using repository-based ETL tools. Those implementing a repository-based ETL tool for the first time will be interested in how to start off in the right direction to support multiple projects. Those who have already implemented such a tool can benefit from this presentation to enhance their support level of data integration projects.

• The Data Integration Environment- What needs to be supported?
• The data integration infrastructure
• Service drivers- What drives the need for processes and procedures
• Data integration support services defined: Standards, change management, metadata, stewardship, auditing, repository administration, pre-existing procedures
• Roles and responsibilities defined: Project level, individual
• When under the gun - Supporting projects in a high-pressure environment

Speaker Comment: This presentation is geared towards corporate practitioners in the data integraiton space, and reflects T. Rowe Price's real-world experiences and hands-on implementation with data integration architectures, process and procedures.

SAP Business Information Warehouse “Top 10 Pitfalls” – What Every DW Professional Must Know

Aaron Zornes
Senior VP, Enterprise Analytics
META Group

Enterprise analytics are increasingly integral to the strategies of both mega application package vendors (Oracle, PeopleSoft, SAP, Siebel) and the G2000 enterprises which deploy these packages. In this presentation, we also summarize future considerations for SAP’s Business Information Warehouse (SAP BW) and related analytic products.

An SAP BW implementation should be treated as a business project rather than an IT project. However, given the limited experience with SAP BW to date, users are well advised to stabilize their R/3 installations prior to putting their SAP BW into production – while benefiting from the lessons learned by other IT organizations. This presentation will cover these key lessons learned for SAP BW initiatives as well as the full “top10” list:

• Provisioning for data quality and data completeness (all data sources)
• Fine-tuning BW InfoCubes and Operational Data Stores
• Understanding and leveraging the SAP BW architecture as part of the SAP R/3 rollout

Department of Defense Net-Centric Data Strategy:
The Right Information, to the Right People, in the Right Format, at the Right Time

Alan Perkins
ASG Federal

Alan Perkins will explain why he believes that the new "Net-Centric Data Strategy" mandated by the DoD Chief Information Officer, coupled with other DoD information management strategies, may be the solution that actually allows mission critical information to be delivered to the right people, in the right format, at the right time. He'll explain what the new requirements are, and how they relate to other new Federal IT initiatives. This session describes:

• ·Department of Defense Architecture Framework (DoDAF)
• ·C4ISR Architecture Data Model (CADM)
• ·Defense Architecture Repository System (DARS)
• ·Federal Enterprise Archicture (FEA)
• ·Net-Centric Data Strategy
• ·How they all relate
• ·The potential and the pitfalls for each
• ·How "industrial strength" metadata management makes it possible

3-D Knowledge Models

Henry Feinman
Information Architect
HJF Infosolve

The structure of Enterprise knowledge is complex – as complicated as any concrete product of our modern organizations. Other areas of endeavour have encountered the problem of complexity: Automotive design, structural architecture, computer chip design. In all these modelling domains the solution has been to use layers, perspective and 3-D CAD to build models that guide creation of these complex objects.

Firstly: Data – Structured and Unstructured, Business rules, Process, Entymologies – which of these belong to our modelling endeavours? What part of Enterprise knowledge is captured by our models, what part remains without?

Next: What alternatives have we for perspective and layering techniques: Data / Process split; Zachman’s enterprise framework; the traditional conceptual / logical / physical; abstraction. What are the strengths and weaknesses of different diagramming methods – ER, UML, ORM?

Finally: we will build sample layers using these techniques and then arrange an optimal set into a 3-D model that more fully renders and communicates the richness of Enterprise Knowledge.

We will step through the model using VRML, parts explosions, and other tools available to modern CAD modellers and see what insights bec