TUTORIALS • 27 October 2003

META DATA TUTORIALS

META DATA FUNDAMENTALS & REALITIES

Peter Aiken Founding Director VCU/Institute for Data Research

IT staff in most enterprises have a common problem. How can they convince managers to invest the resources required to run a REPEATABLE meta data management practice? Internet and intranet technologies are part of the answer and will get the immediate attention of management. XML is the other technology. The current popularity of XML and electronic business technologies has served to rekindle interest in meta data management. On the CMM scale, level three is achieved when organizations benefit from repeatable processes. Organizational meta data management economies are easier achieved at level 3 than at levels below. Metadata engineering in today’s economic climate requires an efficient approach to reconciling business data and jargon using modern data analysis technologies. This tutorial will present required meta data fundamentals in light of the current business realities and continuing gloomy forecasts.

• Metadata
• Definition
• Examples
• Motivation
• Business Case Metadata Engineering
• Defined
• Importance of Modelling
• Recovery techniques
• Objects able to be recovered Metadata Management/ToolKit
• Meta-Meta Model
• Office-Components Metadata Recovery Examples
• ERP
• Reference Metadata
  

INTRODUCTION TO XML FOR DATA PRACTITIONERS

David Plotkin Lead Data Architect Inovant (A Visa Solutions Co)

Data practitioners have known for the past couple of years that XML was a technology that they “must know”. Yet much of the education available to them has been too oriented to the needs of programmers and application developers only, rather than “data people.” At last we’ve solved that problem by asking David Plotkin, a fellow data practitioner, to teach this workshop. This half-day program provides a comprehensive introduction to XML as it relates to various data management functions and responsibilities. It provides an understanding of the importance of XML to meta data management. It will introduce you to the essential aspects of XML-based systems, including DTDs, XML Schema and namespaces. The tutorial will introduce you to the building blocks of XML structures, and also show how to construct DTDs and XML Schemas from reusable components.

• What XML is — from the standpoint of a data practitioner
• What XML is NOT
• The Relational View of XML (which is hierarchical)
• Why Use XML instead of a flat file?
• Understanding the components of a DTD (Elements and Attributes)
• Validating an XML document with a Document Type Definition (DTD)
  Turning a Model into XML
• Understanding the components of XML Schemas (Elements and Attributes)
• Using Namespaces
• Creating reusable XML Schemas
  

META DATA REPOSITORIES: TODAY’S FUNDAMENTALS

Peter Aiken Founding Director VCU/Institute for Data Research

Repository technology managers and those who depend on repositories or should depend on repositories must modernize in order to remain relevant to organizations. This tutorial addresses the following questions. What is the role of the repository in today’s business climate? How does an organization make the business case for an investment in repository technology – especially when starting from scratch? How are repository technologies, metadata management, and XML are inextricably linked? How can you best prepare to leverage these and what can you expect from vendors? What are the related metadata repository and industry trends & standards and what are the implications for repository owners, managers, and users? How are emerging XML standards, vocabularies, and technologies going to impact repository technologies? How can repositories compliment organizational reengineering strategy? How should organizations approach today’s repository implementation?

BEST PRACTICES IN META DATA MANAGEMENT AND ENTERPRISE DATA WAREHOUSE DEPLOYMENT

Stephen Brobst CTO Teradata, a division of NCR

Proper architecture of a data warehouse has a significant impact on the return on investment obtained from its deployment. This tutorial provides a taxonomy of data warehouse topologies and discussion of best practices for enterprise data warehouse deployment. Implementation techniques using integrated, federated, and data mart architectures are discussed along with rules of thumb for when and how to implement these structures as required by analytic applications. Three distinct classes of meta data deployment will be described: design meta data, technical meta data, and semantic meta data. The role of design meta data will be described in the context of creating a single source of truth for enterprise decision making – across multiple lines of business and functionally oriented organizational boundaries. Technical meta data will be described in the context of facilitating ETL/EAI processes for data acquisition and transformation. Semantic meta data will be described as a means of providing accessibility to knowledge workers using business views of data that are specific to each use (without data replication).

• A taxonomy of data warehouse topologies
• role of design meta data
• The role of technical meta data
• The role of semantic meta data
• Quantifying cost and value propositions.
  

ABCS OF INFORMATION QUALITY

Andres Perez President IRM Consulting and Associate of Information Impact Int’l

While organizations have for some time recognized the requirement for quality of products and services to be competitive, most are only now becoming aware of the problems in information quality and how poor information quality hurts both competitiveness and profits. Information quality improvement is not an academic exercise—it is a required tool for business performance excellence in the Information Age.

World-class companies apply the same quality principles, such as Deming’s Fourteen Points, Kaizen and Quality Function Deployment (QFD) to information as a product of business process. This presentation addresses how these principles and techniques apply directly to information as a product and knowledge workers as information customers.
In this tutorial Mr. Perez covers the fundamental principles of information quality. He describes how an organization can improve the quality and value of its information resources. He explains metrics for measuring information quality and management principles for implementing an effective information quality environment. Mr. Perez demonstrates how organizations have successfully implemented information quality processes to improve the effectiveness of their business and information system processes.

A: Assessment: Information Quality Inspection
B: Betterment: Information Quality Improvement
C: Culture: Creating an Environment for Sustainable Information Quality

HOW TO CONDUCT INFORMATION QUALITY PROCESS IMPROVEMENT: Plan-Do-Check-Act Applied to Information Processes

Larry English President INFORMATION IMPACT International, Inc.

Once you have conducted an Information Quality assessment and found unacceptable problems, then what do you do? Sometimes simply conducting an IQ assessment can create immediate behaviour changes and improvement in information quality. Unfortunately, such improvements will only be temporary without discovering and eliminating the root causes of the IQ problems. In this tutorial Mr. English describes how to conduct process improvements (Process P5 of TIQM®) to effect long term and continuous IQ improvement.

You learn how to use Pareto diagrams, Cause-and-Effect diagrams and “Why?” Analysis to discover the root causes of nonquality information. Mr. English describes how you can apply the same principles to improve IQ processes that Shewart, Ishikawa, Deming, Juran, Crosby and Imai applied to improve manufacturing processes.

• Information Quality Improvement and data cleansing are two different things
• Information Quality problems as the symptoms of broken processes
• Categories of IQ problems cause
• Initiating an IQ project
• IQ improvement team make-up
• Using Pareto diagrams for IQ problem prioritisation
• Cause-and-effect diagrams and “Why?” analysis for root cause discovery
• Improving information systems processes to improve data definition quality
• Improving business processes to improve IQ
• The emotional and political ramifications of data quality improvement
• Measuring and documenting ROI for sustainable IQ management
  

INFORMATION MODELLING IN A CHANGING ENVIRONMENT

Graham Witt Senior Consultant AeM Group

Change is an unavoidable feature of every system acquisition project, with requirements not only being refined during the course of the project but frequently evolving into something quite different. Agile methods have evolved in response to this situation but since the tools and techniques generally available to information modellers do not provide much in the way of support for rapid change, it is tempting to dispense with information modelling as if it were an unnecessary and time-wasting distraction. This presentation describes a variety of techniques that enable an information modeller to respond to a changing environment and add value to an agile or conventional project in such an environment. Topics include:

• reasons for change
• managing model changes
• global changes
• model reconfiguration
• consequential changes
• documenting model changes for reviewers
• incorporating changing models in documentation

Half Day Tutorial
9:00-12:30

BUSINESS INTELLIGENCE THE COMPLETE PROJECT LIFE CYCLE

Shaku Atre President Atre Group Inc.

Through 2004, more than 50 percent of Global 2000 enterprises will fail to use BI properly, losing market share to those that implement and leverage BI correctly." However, Gartner analysts say that, "with the right approaches, best practice examples, and the right methodologies, architectures and technologies, enterprises can win big with BI." (Gartner Group; March 19, 2003).

The only way to succeed with BI applications is to understand the complexity of BI applications, their cross-organizational nature, and knowledge workers' information needs, competition, market and customer trends. And to succeed, one needs to be innovative and stand firm in rough waters with an anchor of best practices and the corresponding methodology. And this tutorial will do just that!

Ms. Atre will summarize the 16 steps necessary for the successful design and implementation of Business Intelligence System Applications. Topics discussed include business case assessment, preparing a "balanced scorecard", assessing current solutions, operational sources, and procedures, determining business intelligence objectives, technical and non-technical infrastructure, project planning and delivery requirements, executive dashboard, mobile applications, eCommerce and other potential business intelligence applications, meta data repository analysis, design and development, and implementation.

DATA RESOURCE INTEGRATION

Michael Brackett Consulting Data Architect Data Resource Design and Remodeling

Data integration is a major objective of many organizations. Resolving existing data disparity and creating an integrated data resource is a key strategy for improving data resource quality. However, there are three major problems with current data integration strategies. First, they do not stop the ongoing creation of disparate data before they begin integrating the existing disparate data. Second, they do no integrate all components of the data resource, including data descriptions, structure, integrity documentation, and data management practices. Third, they concentrate only on current problem areas and do not integrate the entire data resource. This tutorial provides the basic concepts, principles, and techniques for stopping the creation of disparate data, resolving the existing disparate data, and creating a high-quality enterprise-wide data resource that is readily shared.

• The current disparate data situation
• The concept of a common data architecture for understanding and integrating data
• The concept of overall data resource quality
• Techniques for inventorying and understanding disparate data
• Techniques for transforming data z Techniques for sharing data

BUSINESS PROCESS MANAGEMENT - INTEGRATION, COLLABORATION AND WORKFLOW

Mike Ferguson European Managing Director Intelligent Business Strategies

This session looks at what is involved in managing and integrating business processes. It looks at why companies are trying to integrate business processes, how to design, model and simulate business processes before deploying them to manage operations

Business (Process Design and Monitoring)
• A BPM methodology • Building blocks for BPM • How to model a business process • Web services and business processes • Business process standardization efforts e.g. BPEL4WS • Enterprise collaboration via B2B business processes • Business process simulation and activity-based costing • Business metrics modelling • Business activity monitoring and analytics generation • Packaged integration – pre-built processes

Technology (Process and Implementation)
• Technology (Process Implementation) • Runtime process and rules engine • Process state management • Interface manager and integration adapter development kit • Security and administration manager • BPM repository • Process driven portals

TO INTEGRATE OR DISINTEGRATE? UNIVERSAL DATA MODELS TO INTEGRATE DATA!

Len Silverston President Universal Data Models L.L.C

How have other organizations been able to integrate data from disparate “silo” data sources? This seminar will share practical models and approaches that have helped many organizations move towards more integrated data. Len Silverston, best selling author of “The Data Model Resource Book, Volumes 1 and 2” will share models to integrate critical data such as customer and product information that may be maintained redundantly in various packaged applications such as Oracle Financials, Siebel, SAP, or custom applications and will share methods showing how to bring this data into a common, integrated data structure. Specifically, this tutorial will address:

• 4 “best practice” data architectures/approaches for integrating data with pros and cons for each
• A Universal Data Model for integrating customer, contact, partner, employee and any other roles played by people and organizations
• A Universal Data Model for integrating products, goods, and services data
• Physical implementation approaches for matching, synchronizing, and integrating data from various sources into a common, integrated data store or data warehouse
• Lessons learned from organizations who have succeeded in integrating data versus those organizations that haven’t succeeded

THE DANGEROUS ILLUSION: NORMALIZATION, INTEGRITY AND PERFORMANCE

Fabian Pascal Data Management Specialist/Editor & Publisher DATABASE DEBUNKINGS

One of the most egregiously abused aspects of information modeling and database design is normalization. Despite the fact that they were repeatedly debunked, arguments against normalization and for denormalization continue to sway practitioners, be they experienced or novices. This costs dearly and reveals the poor understanding of sound design principles by even those who profess to be experts. It is both a major reason for and a consequence of SQL deficiencies and technology regressions such as ODBMS, OLAP, and XML that have come to haunt data management. Even if current data management systems did perform better with denormalized databases, denormalization would still be unjustified, because performance gains, if any, can be had only at the expense of integrity. If the integrity consequences of denormalization are taken into account, they override performance gains, if any.

This workshop demonstrates why the notion of “denormalization for performance” is a fallacy, and exposes its costly implications, of which most practitioners are blissfully unaware:

• What normalization is really about
• The performance illusion behind denormalization
• The integrity implications of denormalization
• The cost of controlling integrity
• Product support of integrity control

ENTERPRISE ARCHITECTURE: STRAIGHT FROM THE SHOULDER

John Zachman President Zachman International

John Zachman has been searching for the Enterprise Architecture “silver bullet” for 30 years and still has not found it. He has given up and says, “there is no such thing as an Architecture Silver Bullet!” In this presentation he includes a brief overview of the Framework for Enterprise Architecture, which establishes a context for:

a. defining precisely what it is about Information Technology that may be causing pain and frustration in the Enterprise these days and therefore,
b. precisely what has to be done to rectify the problems of the past and set a proper course for the future.

John makes the case that architecture is foundational for managing modern enterprises and also develops the engineering logic for integration, usability, reusability, flexibility, interoperability, seamlessness, alignment, reduced time to market, user-friendliness, quality, etc., etc.

Note: this presentation is not for the faint of heart nor for anyone who is looking for a “quick fix” or an “easy out.” This is “Enterprise Architecture, Straight from the Shoulder!”

PROCESS ORIENTATION FOR DATA MANAGEMENT PROFESSIONALS: PROVEN TECHNIQUES FOR ACHIEVING SUPPORT AND RELEVANCE

Alec Sharp Consultant Clariteq Systems Consulting Ltd.

In the years since the tech meltdown, there has been a huge surge of interest in everything to do with “Business Process.” Unlike the near-hysteria of the BPR craze in the early 1990s, when it was often a matter of “jumping under the band wagon,” the current interest is much more reasoned and pragmatic. It’s driven by disappointment with investments in new IT platforms, ERP, e-business, and the “webifiying” of everything. Now, there is a general feeling that by refocusing on business processes, we can achieve the benefits promised by the silver bullets of recent years. To maintain relevance, Data Management professionals must have an understanding of what constitutes “business process orientation.” This presentation will cover proven techniques for introducing a process-oriented focus, and dealing with the associated issues. The central methods and techniques will be described:

• How “re-engineering” become a respectable term again
• Why many of DAMA’s beloved approaches and frameworks can work against process orientation
• What your organization’s processes have in common with every other
• Proven presentation techniques for getting management attention words and phrases to strike from your vocabulary