CONFERENCE
- DAY 1
TUESDAY
8 November 2005 |
| 08:00–09:00 |
|
Registration |
| 08:00–8:45 |
|
International
Association for Information and Data Quality (IAIDQ) Meeting |
| 09:00–09:30 |
|
Joint
Chair Introduction:
Rick van der Lans, Larry
Dziedzic & Larry English |
| 09:30–10:30
|
|
INFORMATION
QUALITY KEYNOTE:
Morning Glories, Mukluks and Mushy Peas: A Systems
Approach to Management
Dr.
Joyce Orsini,
Director, The
W. Edwards Deming Institute |
| 10:30–11:00 |
|
Break
& Exhibit |
| 11:00–12:00
|
META
DATA |
Automated Metadata Utilization
in the BI Envionment
Doug
Stacey, Allstate Insurance Co |
| 11:00–12:00
|
Information
Quality
Track 1 |
IQ
Featured Presentation: Essentials of Effective IQ Management
Larry
English, Information Impact Intl |
| 11:00–12:00 |
DAMA
Track 1 |
Information
Management at Mayo Clinic
Tim
Brennan, Mayo Clinic |
| 11:00–12:00
|
DAMA
Track 2 |
Integrating
the Capital Markets Organisation using XML-Based Standards
Christian
Nentwich, Zulkhe Engineering
Robert James, HSBC |
| 11:00–12:00
|
DAMA
Track 3 |
Enterprise
Architecture: Value Proposition
John Zachman,
Zachman Intl |
| 12:00–
13:30 |
|
Lunch
& Exhibit |
| 12:50–13:20
|
Perspective
Session |
Track
1 - Global
Address: The
Impact of Data Quality in Address Management on International Organisations,
Gordon McGregor, Applications Manager, Sykes & Matthew
Furneaux, Sales & Marketing Director, Global Address |
| 12:50–13:20 |
Perspective
Session |
Track
2 - Trillium Software
- Data Quality for the Enterprise - Examining User Case Studies where DQ
Initiatives Have Delivered major Benefit, Ed Wrazen, Trillium Software
|
| 13:30–14:30
|
META
DATA |
Where
is the Metadata with Generic Information Modelling?
Rick van
der Lans, R20/Consultancy |
| 13:30–14:30
|
Information
Quality
Track 1 |
Information
Quality Supports Performance Targets
Peter Mayhew,
Amec Oil & Gas |
| 13:30–14:30
|
Information
Quality
Track 2 |
Europe,
A Whole Other Ballgame: The Value of
Information Quality in International E-ticketing
Jos de Kruif,
CTS Eventim
Holger Wandt, Human Inference |
| 13:30–14:30
|
DAMA
Track 1 |
Rules
for Requirements Analysis
Ralph
Nijpels, KLM Cargo |
| 13:30–14:30 |
DAMA
Track 2 |
Managing
Synchronised Distributed Data-Sets
Adrian
Miley, Miley Watts LLP
Simon Watts, Miley Watts LLP |
| 13:30–14:30 |
DAMA
Track 3 |
Driving
Down TCO with Data Warehouse Appliances
Tim Young,
Netezza |
| 14:35–15:35 |
META
DATA |
Merging
Companies and Information Reconciliation
Peter
Lawson, MOD
Ken Allen, Skellbase |
| 14:35–15:35 |
Information
Quality
Track 1 |
Mass
Producing Quality Data
Henrik
Liliendahl Sørensen, Consultant
|
| 14:35–15:35 |
Information
Quality
Track 2 |
How
to Perform Information Stewardship within Business Process Redesign
Jim Goetsch,
Schneider National Inc |
| 14:35–15:35 |
DAMA
Track 1 |
Implementing
a Common Data Architecture - a Case Study
Jack
Goodhew, Dover Harbour Board
Keith Gordon, Gordon Blain Associates |
| 14:35–15:35 |
DAMA
Track 2 |
The
Four Pillars of Common Coding
Chris
Maynard, JohnsonDiversey |
| 14:35–15:35 |
DAMA
Track 3 |
The
Role of SOA in Enterprise Data Integration
Jonathan
Carter, Enterprise Architecture Solutions |
| 15:35–16:05 |
|
Break
& Exhibit |
| 16:05–17:05
|
META
DATA |
Experiences
in Using the IBM Banking Models for Financial Datawarehousing
Leon Gütz,
Rabobank |
| 16:05–17:05 |
Information
Quality
Track 1 |
How
Yell Ltd Increased IQ While Saving Money
Gerry
Rankin, Yell
Greg Larsen, Harte Hankse |
| 16:05–17:05 |
Information
Quality
Track 2 |
Data
Quality and Basel II: Where Does it Start?
Mark
Dunleavy, Similarity Systems |
| 16:05–17:05 |
DAMA
Track 1 |
Using
Information Management to Manage Risk
John
Ladley, KI Solutions
|
| 16:05–17:05 |
DAMA
Track 2 |
Using
the Scorecard to improve Data Model Quality
Steve Hoberman, Mars |
| 16:05–17:05 |
DAMA
Track 3 |
Implementing
Enterprise Data Management in a Local Council
John Anderson, Ealing
Council |
| 17:05–18:45 |
|
Drinks
Reception & Exhibit |
| 17:30–18:00 |
Perspective
Session |
Track
1 - Similarity
Systems - Analyse, Align, Cleanse, Sustain: The step-by-step
approach to achieving Data Quality, Garry
Moroney, CEO, Similarity Systems |
| 18:05–18:35 |
Perspective
Session |
Track
1 - Datanomic
- Steve
Tuck, Chief Strategy Officer, Datanomic |
| 18:45-19:45
|
DAMA |
DAMA
UK MEETING |
| |
| Tuesday
8 November
09:30–10:30
 Back
to top
|
INFORMATION
QUALITY Keynote:
Morning
Glories, Mukluks and Mushy Peas: A Systems Approach to Management
Dr.
Joyce Orsini,
Director, The W. Edwards Deming Institute
Through
metaphors and examples, Dr. Joyce Orsini will discuss the benefits of running
an organization as a system. She will compare and contrast a systems approach
to management with what exists in many companies today. She will discuss
the interdependence of the different functions of the organization and how
barriers between functions create suboptimal behavior and results. Conflicting
goals, confusion, diffusion, and displacements result in poor performance
and chaos. Ongoing chaos (stable chaos) is sometimes difficult to uncover,
as it is repeatable, easy to document, and eligible for ISO status. Points
will be clarified through examples from organizations with which Dr. Orsini
has worked.
- The organization
as a system
- Optimization of
a system
- Losses from the
prevailing system of management
- Suboptimal company
practices
- Relationship between
strategies, policies and procedures
|
Featured
Speaker:
|
| CONCURRENT
SESSIONS |
| Tuesday
8 November
11:00–12:00
META DATA
Back
to top |
| CASE
STUDY |
 |
 |
Automated Metadata
Utilization in the BI environment
Doug Stacey,
Manager, Data Management, Allstate Insurance
Allstate
Insurance has been a two-time recipient of the Wilshire Award including
“Outstanding Data Warehouse Meta Data Implementation”. This
presentation will give an overview of the Managed Meta Data Environment
at Allstate Insurance with a focus on the utilization of meta data in
the Business Intelligence environment. The flow of data from point of
capture, to a central repository, through an XMI based bridge into the
Business Intelligence tool, and ultimately to the end user, will be covered.
-
Overview of Allstate’s Managed Meta Data Environment
-
Input to the Meta Data Repository
-
Preparation of the Meta Data
-
High Level Architecture
-
Use of the Meta Data Bridge and XMI
-
Meta Data Interaction with BI tool
-
Examples of End User Experience
|
Featured
Speaker:
 |
|
Doug
Stacey
Manager, Data Management
Allstate Insurance
|
|
| Tuesday
8 November
11:00–12:00
Information
Quality
Track 1
Back
to top |
IQ
FEATURED PRESENTATION: Essentials of Effective Information Quality Management
Larry
P. English, President, Information Impact International,
Inc.
“Information
Quality” functions are more prominent than ten years ago. But, one
must understand what IQ means in order to call a function “Information”
or “Data Quality Management.” To be effective and sustainable,
an IQ or DQ function must conform to the same quality principles and practices
that transformed manufacturing quality. The maturing of manufacturing
Quality Management systems have paved the way for IQ management.
In this presentation,
Mr. English describes the essential and fundamental principles of Information
Quality Improvement processes for maximum benefits and business effectiveness.
Illustrations from organizations around the world that have implemented
successful information quality processes, Mr. English describes the techniques
and cultural transformation required for an effective and sustainable
Information Quality environment.
- Drivers demanding
IQ management
- What Information
Quality Management is and is not: Dispelling the myths
- Core processes
- Focusing on the
“Customer”
- Core competencies
in the Information Age
|
Featured
Speaker:
|
| Tuesday
8 November
11:00–12:00
DAMA
Track 1
Back
to top |
| CASE
STUDY |
|
|
Information Management at
Mayo Clinic
Tim Brennan,
Data Administrator, Mayo Clinic
Is
your organization struggling to integrate data? Is there a lack of consistent
metadata and use of data elements in your organization? If questions like
these elevate your blood pressure, this story is for you! This is the story
of an ongoing journey Mayo Clinic is undertaking and the lessons learned
along the path of the journey to IM.
- Program Objectives
- Common Data Architecture
- Infrastructure
and Stewardship
- Operational Support
- Power, Politics
and Change
|
Featured
Speaker:
|
| Tuesday
8 November
11:00–12:00
DAMA
Track 2
Back
to top |
| CASE
STUDY |
|
|
Integrating the Capital Markets Organization using XML-Based Standards
Christian
Nentwich, Senior Consultant, Zuhlke Engineering Limited
Robert James,
Data Architect, Corporate, Investment Banking and Markets
HSBC Group
Many
organizations in the capital markets are seeking to improve the efficiency
of their business operations in order to reduce costs, increase margins
and provide better customer service. This presentation will explain how
many leading organizations in the capital markets are starting to achieve
effective data integration by embracing 3rd party XML-based data standards
such as FpML, FIXML and MDDL. The benefits and challenges to this approach
will be explained using a real case study from HSBC. This presentation should
be of benefit to any organization implementing third-party data standards.
|
Featured
Speakers:
|
| Tuesday
8 November
11:00–12:00
DAMA
Track 3
Back
to top |
Enterprise
Architecture: Value Proposition
John Zachman,
President, Zachman International
Most
People still think the way to acquire funding for new systems is “cost-justification”.
I would suggest that the Value Proposition for systems has radically changed.
There are four reasons you “do” Architecture including alignment,
integration, change management and reduced time to market. Without Architecture,
there is NO WAY you can do any of these things. This presentation begins
with a brief tutorial on the Framework for Enterprise Architecture and then
develops the logic as to its value to the Information Age Enterprise. |
Featured
Speaker:
|
| |
| Tuesday
8 November
13:30-14:30
META DATA
Back
to top |
Where is the
Metadata with Generic Information Modelling?
Rick F. van der Lans,
R20/Consultancy B.V.
The
goal of generic information modelling is to create more adaptive and flexible
information models through techniques such as avoiding overnormalisation,
separating structure from integrity, and generalising models. Too often
the moment information needs change, the information model, the database
structure and the application code have to be changed. But there is a serious
impact on metadata. Most of the metadata will end up in business rules instead
of classic structural concepts. This presentation highlights the importance
of generic modelling and explains the impact on metadata management.
- what exactly is
generic information modelling?
- normalisation
is OK, overnormalisation isn’t
- how do we separate
integrity rules from structure?
- meta data in the
form of business rules
|
Featured
Speaker:
|
| Tuesday
8 November
13:30-14:30
Information
Quality
Track 1
Back
to top |
| CASE
STUDY |
|
|
Information Quality Supports
Performance Targets
Peter
Mayhew, Information Manager, AMEC Oil and Gas
AMEC
Oil and Gas developed a strategic information management infrastructure
to provide high quality data and documents for all major projects. With
every customer project relying on vast amounts of accurate, complete and
fit for purpose information, data quality is at the heart of each project
and is considered competitive advantage.
AMEC transformed its business processes with an internal information management
system and IQ software. The company’s data quality function is part
of corporate strategy. You learn:
- Why AMEC took
a long-term, strategic approach to DQ
- How they transformed
traditional and manual business processes
- How they managed
cultural change
- How they applied
initial successes of one project to make it part of corporate strategy
|
Featured
Speaker:
|
| Tuesday
8 November
13:30-14:30
Information
Quality
Track 2
Back
to top |
| CASE
STUDY |
|
|
Europe, A Whole Other Ballgame:
The Value of Information Quality in International E-ticketing
Jos de Kruif,
Ticketing Manager, CTS Eventim
Holger Wandt,
Principal Advisor, Human Inference
With
over 120 million practitioners and even more active fans, football is by
far the most popular sport in Europe.
Organizing events like European or World soccer championships holds significant
challenges in managing the enormous fan crowd. Issues for such an event
include: Identification of ticket fraud, Black list matching, Country-specific
internet templates for ticket purchase and International name and address
data design
You learn the problems encountered in the organization of large events and
how to solve them, to improve process efficiency and reduce risk:
- Name / address
quality and duplicate matching
- IQ in Web content
and e-business (B2C) design
- Data model quality,
CRM and IQ
- Data Enhancement
and IQ
|
Featured
Speakers:
|
| Tuesday
8 November
13:30-14:30
DAMA
Track 1
Back
to top |
| CASE
STUDY |
|
|
Rules for Requirements Analysis
Ralph Nijpels,
Business Analyst, KLM Cargo
In
2002-03 KLM Cargo did a post mortem on projects that did not return their
projected benefits. The analysis turned up a pattern. The software was built
as designed, of reasonable quality, on time, and within budget. However,
a large number of functional changes were needed to fulfill changed or missing
requirements. Here are the essential improvements made to Process Requirements,
Information Requirements, and Business Rule Requirements that re-enforced
each other and helped create a better business model including:
- Scenario Thinking
Improvements
- Applying Conceptual
Modeling Techniques
- Asking “Why”
to Obtain Business Rules
|
Featured
Speaker:
|
| Tuesday
8 November
13:30-14:30
DAMA
Track 2
Back
to top |
| CASE
STUDY |
|
|
Managing Synchronized Distributed
Data-Sets
Adrian
Miley, Senior
Partner, Miley Watts LLP
Simon Watts,
Senior Partner, Miley Watts LLP
In
any distributed data environment there will be a number of standard problems
that need to be addressed in order to integrate the data-sets into a single
coherent whole. Strategies for synchronizing data in geographically distributed
organizations or organizations that are actively acquisitive will be discussed
with a focuses on:
- Defining terms
- Problems of cross-referencing
business entities
- Translations between
Public and Private identifiers
- Identifying key
issues and options for resolution
|
Featured
Speakers:
|
| Tuesday
8 November
13:30-14:30
DAMA
Track 3
Back
to top |
Driving Down
TCO with Data Warehouse Appliances
Tim
Young, Director, Netezza
As
data volumes continue to grow and IT budgets continue to shrink, companies
face the challenge of increasing their analysis capabilities but with fewer
resources. A solution receiving much attention is that of the “data
warehouse appliance”. Through an architecture optimized for data warehousing
and a construction almost entirely from commodity parts, these appliances
look set to alter the landscape of business intelligence. This presentation
answers the following questions drawing from real world experiences:
- What is a DW appliance
and when should they be considered?
- What savings typically
accrue and from where?
- What impact are
they having on organizations?
- What are the key
stages of implementation?
|
Featured
Speaker:
|
| |
| Tuesday
8 November
14:35–15:35
META DATA
Back
to top |
| CASE
STUDY |
|
|
Merging Companies and Information
Reconciliation
Peter
Lawson, Information Analyst, MOD
Ken Allen, Partner,
Skellbase
Merging of companies
and organisations invariably involves the need to examine the information
required to carry out the future business and the information systems that
support the business. Reconciliation of systems requires a detailed understanding
of the information needed to perform the activities of the merged organisation
and the information held in disparate information systems. This presentation
will discuss the use of information models as the basis for the integration
of information systems allowing decisions to be made from a position of
knowledge.
- Why information
models?
- How to create
an information model.
- Merging information
models.
- The role of merged
and unmerged information models in the reconciliation of data stores.
- Risk reduction
and associated costs.
|
Featured
Speakers:
|
| Tuesday
8 November
14:35–15:35
Information
Quality
Track 1
Back
to top |
Mass Producing
Quality Data
Henrik
Liliendahl Sørensen,
Consultant
A
method for jump starting name and address data quality is letting a specialized
service provider clean, profile, match, enrich and de-duplicate your records.
In such an environment they practically mass produce quality data. Learn
about some of the principles, methodologies and technologies involved in
this work. These principles include:
- Comprehensive
utilization of all possible data elements and sources
- Optimal utilization
and support for limited human inspection
- Implementation
of learning capabilities
|
Featured
Speaker:
|
| Tuesday
8 November
14:35–15:35
Information
Quality
Track 2
Back
to top |
| CASE
STUDY |
|
|
How to Perform Information
Stewardship within Business Process Redesign
Jim Goetsch,
Data Architect, Schneider National, Inc.
This
presentation describes how Schneider implemented an ‘information stewardship’
approach to ensure information quality within and across business processes
being redesigned. Experience how our organization learned that information
is the glue that integrates business processes.
- Where Information
Stewardship fits within Business Process Redesign
- Five phases (including
deliverables) of Information Stewardship
- Illustrate accomplishments
in a real-life BPR effort
The illustration includes
the old and new process, conceptual data model, information policies,
required information quality levels, process life-cycle states among others.
The business gained the ability to maintain satisfactory quality at the
entity/attribute level. A real life example illustrates the redesign of
our ‘Accept the Transportation Order’ process. |
Featured
Speaker:
|
| Tuesday
8 November
14:35–15:35
DAMA
Track 1
Back
to top |
| CASE
STUDY |
|
|
Implementing a Common Data
Architecture
Keith
Gordon, Gordon Blain Associates Limited
Jack Goodhew,
Dover Harbour Board
The
Dover Harbour Board was seeking help with the design of a 'large database'.
However, having discussed the problem with the analysts and developers in
the ICT Department of the Dover Harbour Board, it became clear that there
was a deeper problem. The development of a Common Data Architecture was
proposed to inform, and assist with, all future system development, and
the proposal was accepted. But, how did it work out in practice? This presentation
will cover:
- How the Concept
of a Common Data Architecture was 'Sold' by the Consultant to the Client.
- The Approach for
the Development of the Common Data Architecture.
- The Progress so
far from the Consultant's Perspective.
- The Progress so
far from the Client's Perspective.
|
Featured
Speakers:
|
| Tuesday
8 November
14:35–15:35
DAMA
Track 2
Back
to top |
| CASE
STUDY |
|
|
The Four Pillars of Common
Coding
Chris
Maynard, Global Data Architect, JohnsonDiversey
This session focuses
on the experience of one multi-national, Johnson Diversey, in moving toward
one code for one SKU - everywhere. The lessons learned are applicable to
any initiative to eliminate duplicate and conflicting coding. Using this
technique, Data Architecture, Data Management and IT Development all fit
together for a complete solution and far less time is wasted on fruitless
discussions and manipulation of coding. This session addresses the four
key requirements for common coding and answers the question, “When
is common coding a vital business enabler, and when is it an unacceptable
business overhead? |
Featured
Speaker:
|
| Tuesday
8 November
14:35–15:35
DAMA
Track 3
Back
to top |
The Role of
SOA in Enterprise Data Integration
Jonathan
Carter, Principal Architect, Enterprise Architecture Solutions
For any large organization
a “top-down”, enterprise view of information is essential for
managing the data that is inevitably shared across diverse systems. However,
in practice this has proved difficult as the multiple views of data are
often specific to the technology with which the data is managed, e.g. RDBMS,
XML Schema. The concept of the Service provides an approach to regain a
single view by separating the “what” (Information) from the
“how” (Technology). |
Featured
Speaker:
|
| |
| Tuesday
8 November
16:05–17:05
META DATA
Back
to top |
| CASE
STUDY |
|
|
Experiences in Using the IBM
Banking Models for Financial Datawarehousing
Leon Gütz,
Rabobank
The
Rabobank has been developing a central data warehouse for some time now.
Their primary goal is to decouple information flows between basic operational
systems, to support internal and external reporting, and to facilitate marketing.
Development is based heavily on the IBM models FSM Financial Services Data
Model) and BDWm (Banking Data Warehouse model), both part of the Information
Framework (IFW).
- General structure
and layering approach of the models - how are those models used by the
Rabobank?
- How do you get
insight in and how do you manage the information flows?
- The importance
of standardisation based on reference models.
- What role does
metadata play with implementing new regulations such as Basel II and
IFRS
- The crucial role
of metadata when working with reference models
|
Featured
Speaker:
 |
|
Leon
Gütz
Information Manager Data
Rabobank Group ICT
|
|
| Tuesday
8 November
16:05–17:05
Information
Quality
Track 1
Back
to top |
| CASE
STUDY |
|
|
How Yell Ltd Increased IQ
While Saving Money
Gerry Rankin,
Information Architecture Principal, Yell, Ltd.
Greg Larsen,
Data Management Principal, Harte Hanks Ltd.
Managing
a 4 million record Customer and Prospect database with 50,000 weekly updates
is always a major Information Quality challenge. Yell Ltd. implemented the
SAP R/3 system two years ago and quickly noticed the costs of duplicate
records, poor address quality, and customer dissatisfaction.
Yell implemented improved data cleansing rules reducing duplicates by 80%.
Manual processing is now down to about 300 records per week. Annual savings
are estimated to be £1,000,000, surpassing the cost of implementing
the project in the first few months of operation. You learn:
- Data management
processing in large and growing B2B databases
- IQ best practices
in a combined Batch / Online application
- Increase IQ while
decreasing cost of nonquality
|
Featured
Speakers:
|
| Tuesday
8 November
16:05–17:05
Information
Quality
Track 2
Back
to top |
Data
Quality and Basel II: Where Does it Start?
Mark
Dunleavy, Manager, Financial Services, Similarity Systems
Basel
II implementation projects expose significant risk issues in the infrastructure,
including policy, processes, systems and Data Quality. The Data Quality
problem is so widespread that most analysts agree that the lack of access
to high Data Quality can be the greatest obstacle to compliance. And Data
Quality issues extend beyond risk management systems to the financial and
regulatory reporting systems. Using
Similarity Systems’ Data Quality management product ATHANOR, you
learn:
- A framework methodology
for Data Quality
- An automated approach
to data accuracy with a transparent audit trail
- Automating data
quality results and taking steps towards corrective action
|
Featured
Speaker:
|
| Tuesday
8 November
16:05–17:05
DAMA
Track 1
Back
to top |
Using
Information Management to Manage Risk
John Ladley,
President, KI Solutions
There
is a strong case to be made that the number one topic for IT is Risk Management.
This is evidenced by the spate of legislation the past few years. At the
heart of regulatory related IT efforts are the assessment of good old-fashioned
controls, privacy and security functions. This session will present what
is really happening above the glass ceilings in terms of risk management,
and how IM can truly position itself for value added work in the area of
managing risk. Topics will be:
- Compliance Still
Leaves Risk
- Regulatory Compliance
- Financial Risk
of Poor IM
- How to Apply IM
for Risk Mitigation?
- Basic Risk Metrics
and Controls
|
Featured
Speaker:
|
| Tuesday
8 November
16:05–17:05
DAMA
Track 2
Back
to top |
| CASE
STUDY |
|
|
Using the Scorecard to Improve
Data Model Quality
Steve
Hoberman, SAP Functional Analyst, Mars, Inc.
Aim,
wind, and gravity influence an arrow’s trajectory, much the same way
as deadlines, skills, and biases influence a data model’s trajectory,
strongly impacting whether a model will reach its target of accuracy, longevity,
practicality, and consistency. The Scorecard contains all of the criteria
for highlighting strengths and identifying weakness in our designs. This
presentation will go into detail on the Scorecard, and provide techniques
and tips for improving the quality of your model such as:
- Measuring Data
Model Quality
- Explaining the
Scorecar
- Leveraging Techniques
to Strengthen Models
- Introducing the
Scorecard into a Company Culture
|
Featured
Speaker:
|
| Tuesday
8 November
16:05–17:05
DAMA
Track 3
Back
to top |
| CASE
STUDY |
|
|
Implementing Enterprise Data
Management in a Local Council
John
Anderson, Business Architect, Ealing Council
The
session will link the centrality of Data Management to becoming a customer
focussed organisation which is being transformed from end-to-end. There
will be a description of the council's Enterprise Logical Data Model, unique
in local government, as part of an Enterprise Information Architecture,
its relationship to process re-design and building of new ICT platforms.
|
Featured
Speaker:
|
Tuesday
8 November
18:45–19:45 DAMA
Back
to top |
DAMA UK
MEETING
A
meeting of the DAMA UK Chapter will be held Tuesday evening. Members of
the DAMA UK Chapter, anyone interested in becoming a member of the DAMA
UK chapter, and anyone interested in learning more about DAMA may attend
the meeting. David Evans, Chair of DAMA UK, DAMA UK Board members, DAMA
International Board, and the DAMA International Advisory Board will be present
to answer questions. The results of the elections for DAMA UK Committee
Members will be announced. You do not need to be registered for the Conference
to attend the DAMA meeting, so please invite colleagues to attend. For more
information visit www.damauk.org. |
