Compiled and edited by Tony Shaw, Program Chair, Wilshire Conferences, Inc




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НазваниеCompiled and edited by Tony Shaw, Program Chair, Wilshire Conferences, Inc
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Kent Graham, O'Melveny & Myers LLP


David Schlesinger, Intel

Simon Hankinson, PWC

David Newman, RadioShack


This presentation discussed the requirements of Sarbanes Oxley and how the data management organization can effectively help the organization meet its the compliance requirements. This is a new area to most DM professionals, but there are many opportunities to help the CIO, the Applications Services organization, and the Internal Audit Group with compliance.


RadioShack for example is focusing on 3 areas of support: 1) data quality (is the data on your annual statement accurate?); 2) data modeling and data transformation (what does the data on your annual statement mean?); 3) metadata management and governance/stewardship (where did the data on your annual statement come from and who’s responsible for it?).


Suggested questions to be addressed by the DM organization are:

  • What services should data management organizations provide to their companies to help meet the compliance objectives of Sarbox?

  • What role does data quality play in Sarbox?

  • What role does data modeling and data transformation play?

  • What role does metadata management and data stewardship play?

  • What data governance policies need to be implemented for Sarbox?



CONFERENCE SESSIONS

Wednesday, May 5

11:10 am – 12:10 am


Practical Experience with Enterprise Data Modeling


John Sykes

Manager

The Vanguard Group


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


Successes:

Adopting a maturity model for enterprise database evolution to establish a vision and temper expectations.

Setting clear and measurable objectives for the data modeling team.

Utilizing Reverse-Engineering to jump-start models.

Adopting "structured agile" data modeling techniques.

Embracing continuous process improvement.


Pitfalls:

  • The desire for "top-down modeling".

  • Dealing with conversion and interface teams.

  • Analysis Model (Class Diagrams) vs Logical Data Model Dilemma.

  • Insufficient Metadata for knowledge sharing.



Enterprise Architecture: A Strategic Approach to Improving Data Quality and Restructuring Information Management


Jorge Yero

Business Intelligence and Reporting Team Lead


Aera Energy LLC


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


The Table Management Distribution System:

Air Mobility Command’s Reference Data Success Story


Charles Capples

Senior Information Systems Engineer
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