marcus Evans data quality conference Paul Ormonde-james key speaker on data quality and solving the applications issues. A practical guide from his time at MBF Australia.

1. Data Quality
From Theory to Practice
MARCUS EVANS CONFERENCES
Paul Ormonde-James
Group Intelligence
MBF Australia

2. Agenda
• Why is data quality important?

3. The problem to be solved…..
Target
You
are
here

4. The problem to be solved…..
Target
You
are
here

5. Paul Ormonde-James – Presenter, Speaker, Author
• Paul, has spent many years in the field of
Change Management. He has
qualifications in Cybernetics (Robotics &
Artificial Intelligence), Computer Sciences,
a Master of Business Administration (MBA)
and post grad in Company Law. He has
driven many change programs and used
Business Intelligence, Competitive
Intelligence and Knowledge Management
to drive such cultural change to increase
company value.

6. Business Intelligence, simply…..
Corporate Survival & Growth
“Growing through Knowing”
More effective decision making
At the
To the

8. Business BI

9. Why do we need data quality?
• There is a growing cross-industry recognition of the value of
high-quality data.
• 2001 PricewaterhouseCoopers Global Data Management
Survey, 75 percent of the senior executives reported significant
problems as a result of defective data.
• In 2002, The Data Warehousing Institute published its Report
on Data Quality in which they estimated that the cost of poor
data quality to U.S. businesses exceeds $600 billion each year.
• Two critical pieces of legislation passed within the past few
years impose strict information quality requirements on both
public corporations in the U.S. (the Sarbanes-Oxley Act of
2002)
• As well as U.S. federal agencies (The Data Quality Act of
2001).
• Both of these laws require organizations to provide auditable
details as to the levels of their information quality.

10. Do Managers really understand data quality?????
• How many times does a manager or executive ask
where the data comes from?
• How many executives understand the numerous
data sources in and across an organisation
• How many Executives understand the errors
generated as incorrect data is summarised.
• Are executives more focussed on quality data the
more important the decision?