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Keynote for MDM SUMMIT Fall 2008 in NYC April 25, 2009

Posted by Peter Benza in 1, Data Governance, Data Hygiene, Data Integration, Data Management, Data Stewardship, Linkedin.
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As part of some ongoing research I have been conducting, here is a slide deck I came across from 2008 – the keynote for the CDI-MDM Summit this past fall in NYC. Re: Key Trends

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Dots On A Map Improve Data Quality April 18, 2009

Posted by Peter Benza in Data Accuracy, Data Hygiene, Data Integrity, Data Management, Data Mining, Data Profiling, Data Quality, Data Standardization, Data Stewardship, Data Types, Data Visualization, Linkedin.
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This was a presentation I originally prepared back in 2005, but is probably even more applicable in 2009 given the impact using a GIS tool can have on visualizing data quality – customer addresses on  a map! The next time you conduct a customer “data” assessment – try this!

Cognos data quality rapid assessment service January 17, 2008

Posted by Peter Benza in Data Accuracy, Data Analysis, Data Governance, Data Integration, Data Management, Data Metrics, Data Profiling, Data Quality, Data Standardization, Data Stewardship, Data Tools.
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http://www.cognos.com/performance-management/technology/data-quality/pdfs/fs-cognos-data-quality-rapid-assessment-service.pdf

SOA Governance At Bea: Essential to your enterprise transformation strategy January 17, 2008

Posted by Peter Benza in 1, Data Analysis, Data Architecture, Data Governance, Data Integration, Data Management, Data Optimization, Data Profiling, Data Security, Data Stewardship.
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Effective SOA governance is an essential element in any enterprise transformation strategy. It can help your organization achieve measurable, sustainable business value.

Read about this and other webcasts, whitepapers, etc… at Bea.

http://www.bea.com/framework.jsp?CNT=index.jsp&FP=/content/solutions/soa_governance/

Summit 2008 – San Francisco January 10, 2008

Posted by Peter Benza in Data Accuracy, Data Governance, Data Integrity, Data Metrics, Data Processes, Data Quality, Data Stewardship, Data Strategy, Data Templates, Data Verification, Data Warehouse.
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If you have not attended a Summit then mark your calendars for:

CDI-MDM Summit Spring 2008

Please post and share your comments about this upcoming summit or if you have not attended and want to learn more then link using the above reference.

MDM Accelerator® by Zoomix January 9, 2008

Posted by Peter Benza in Data Accuracy, Data Aggregates, Data Analysis, Data Assessment, Data Consolidation, Data Dictionary, Data Formats, Data Governance, Data Hygiene, Data Integration, Data Management, Data Metrics, Data Processes, Data Profiling, Data Quality, Data References, Data Sources, Data Standardization, Data Stewardship, Data Synchronization, Data Templates, Data Tools.
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To learn more about or post your comments about MDM Accelerator®

by Zoomix.

http://www.zoomix.com/mdm.asp

Teradata – Master Data Management January 9, 2008

Posted by Peter Benza in Data Assessment, Data Consolidation, Data Dictionary, Data Governance, Data Hygiene, Data Integration, Data Management, Data Metrics, Data Processes, Data Profiling, Data Quality, Data Standardization, Data Stewardship, Data Strategy, Data Templates, Data Tools, Data Types.
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To learn more about Teradata and their MDM solution offering:

http://www.teradata.com/master-data-management

International association of information and data quality website September 19, 2007

Posted by Peter Benza in Data Governance, Data Hygiene, Data Management, Data Quality, Data Stewardship.
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www.iaidq.org

What is the first piece of advice you would give someone starting a data governance program? September 18, 2007

Posted by Peter Benza in Data Governance, Data Management, Data Metrics, Data Stewardship, Data Strategy.
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The link between Data Quality and Data Governance September 18, 2007

Posted by Dan Power in Data Governance, Data Quality, Data Stewardship.
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I suppose it’s possible to have an enterprise data quality program without having a data governance program.  But I think having an enterprise-wide data governance program which includes data quality as one of its core focus areas makes more sense.

Data quality without data governance means having to correct the same errors over and over again, and not fixing the problem at the source. But data quality with data governance means bringing the data governance council up to speed on the issue, inviting the different business owners to present their views, and then defining a solution that will be funded, supported and enforced.

Data quality without data governance can be a “solution in search of a problem” – where an IT department adopts data quality tools without directly involving the business, and applies them “in the back room” so to speak.  But data quality tools within the context of a corporate data governance program means the business is fully involved from the beginning, from forming the data governance council, to staffing the data management organization with business data stewards, to providing some or all of the funding, etc.

I’ve been encouraging clients lately to start by defining a data governance program, then to build the data governance council and the attending processes, then to start thinking about individual projects underneath the banner of the data governance program.  That could include projects like implementing specific data quality tools or a Master Data Management hub.

The holistic approach that I generally recommend recognizes that for most business problems, there’s going to be:

  • a People aspect (requiring organizational change, with impacts on corporate culture, accompanied by a political dimension)
  • a Process aspect (as the organization realizes that treating information as a true corporate asset means some new work is going to have to be done by someone)
  • a Technology aspect (usually requiring new platforms, applications or tools)
  • an Information aspect (enriching internal data with trusted external content, for example)

This holistic approach to data governance usually involves wholesale improvements in data quality and in integration. If you want to better capture, store, manage and use information, you’re going to need better data entry procedures, better integration between applications and databases, and an efficient, automated way to find & correct incorrent data.

But you’re never going to be able to get away from the People side of things.  People need to be convinced of the importance of data quality as an issue, and of the need for a comprehensive data governance framework as the best long term way to fix data quality problems.

What department should data stewards reside in… IT or business? August 19, 2007

Posted by Peter Benza in Data Governance, Data Stewardship.
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Peter Benza – 1984 graduate of the direct marketing educational foundation – creates enterprise data quality weblog August 13, 2007

Posted by Peter Benza in Data Elements, Data Governance, Data Integrity, Data Management, Data Mining, Data Optimization, Data Profiling, Data Quality, Data Stewardship, Data Strategy, Data Tools, Data Variables, Data Visualization.
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