Underpinning all data management initiatives is the fundamental need to get data quality right. Poor data quality can be costly, impact customer service, lead to errors in risk management and regulatory reporting, and more. So, how can you improve data quality? How can you use rules, standardisation and technology to make improvements? And how is ‘right’ data quality measured?
Listen to the webinar to find out about:
Requirements for data quality
Challenges of achieving data quality
Data quality metrics
Supporting tools and technology
Operational and business gains
1. FROM
DataManagementReview.comSeptember 21, 2016
Approaches to data quality
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If you’re a vendor looking for high quality content to help articulate your message, take a look at www.a-
teamgroup.com. Or get in touch: 020 8090 2055 / theteam@a-teamgroup.com
4. FROM
DataManagementReview.comSeptember 21, 2016
Panel Member: Sue Geuens, Data Standards and Best
Practice Adoption, Barclays, and President, DAMA
International
Areas of Expertise:
• Became owner of all data for Nhbrc in South Africa when
it started in 2006 and learned about quality the hard way
• Original creator of algorithms defining data quality
criteria for a South African data quality tool, Plasma Mind
• Since then, at almost all clients have been involved in data
quality programmes and assisting with data quality strategies
• Operational expertise of many data quality tools
5. FROM
DataManagementReview.comSeptember 21, 2016
Panel Member: Matthew Rawlings, Head of Middle Office
and Operations, Bloomberg L.P.
Areas of Expertise:
• Assessing data risk and operational controls
• Financial data technology
• Industry data utilities
6. FROM
DataManagementReview.comSeptember 21, 2016
Panel Member: Dominique Tanner, Head of Business
Development, SIX Financial Information
Areas of Expertise:
• Lead major initiatives to implement strategic measures to
ensure high data quality standards
• Delivered efficiencies by aligning data flows between
service providers and users
• Industry advocate for the evolution of the data
management ecosystem
7. FROM
DataManagementReview.comSeptember 21, 2016
The definition and importance of data quality
Business cases driving data quality improvement
The challenges of achieving data quality
Best practices for data quality implementation
Technologies to support improvement
Metrics for data quality measurement
Operational and business benefits
Talking Points
22. FROM
DataManagementReview.comSeptember 21, 2016
Thank you to our sponsors
Contact:
Dominique Tanner
Head Content Management
SIX Financial Information
dominique.tanner@six-group.com
Contact:
Matthew Rawlings (New York)
mrawlings1@bloomberg.net
+1 646 324 4460
Andrew Parry (London)
aparry22@bloomberg.net
+44 20 3525 9425
24. FROM
DataManagementReview.comSeptember 21, 2016
Upcoming A-Team Group Webinars
September 29th
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data lineage
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October 13th
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KYC systems
Visit webinars section of DataManagementReview.com