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Human Inference – an international data quality solution provider February 11, 2008

Posted by Peter Benza in Data Governance, Data Hygiene, Data Integrity, Data Management, Data Metrics, Data Processes, Data Profiling, Data Quality.
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From the website:

Human Inference discovered that to reach the desired results, mathematical logic is not sufficient. The knowledge about the language and culture of a country was necessary as well. Human Inference proved to be right, since today the largest companies of the world are using our knowledge-based software to improve the quality of their data.

http://humaninference.com/services/professional-services/data-quality–assessment/

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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

Innovative Systems, Inc – data quality assessment tool January 14, 2008

Posted by Peter Benza in Data Assessment, Data Errors, Data Governance, Data Hygiene, Data Metrics, Data Processes, Data Profiling, Data Tools.
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http://www.innovativesystems.com/services/data_quality_assessment.php

The Innovative Data Quality Assessment provides a quick and economical evaluation of the quality of your customer information. It identifies areas where your information may be enhanced or improved, and quantifies the impact of the defined data quality issues in terms of costs, customer service, lost revenues, etc. It also benchmarks your organization’s data quality against industry standards, showing how your data quality compares to others in your industry.

What types of common data problems are found in your master data? January 13, 2008

Posted by Peter Benza in Data Analysis, Data Assessment, Data Governance, Data Hygiene, Data Metrics, Data Profiling, Data Quality.
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Master Data exists across your entire enterprise.  Companies today are assessing what is the best way to consolidate all their information assets (data sources) into a “single customer view”.

What types of data problems exist in your organization today or the future with the move towards managing data at the enterprise level?

[Be first to answer this question]

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

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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(Be first to author an article on this topic.)

Cognos to resell Informatica’s data quality software September 16, 2007

Posted by Peter Benza in Data Assessment, Data Management, Data Metrics, Data Profiling, Data Quality, Data Strategy.
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The services are grounded on a data quality assessment summary that comprises quality reports, best practices, and recommendations.

http://www.cbronline.com/article_news.asp?guid=63BF0934-3590-4C07-9E4D-02D7BC7CB060

What metrics do you use to monitor data quality in your organization? September 16, 2007

Posted by Peter Benza in Data Metrics, Data Quality, Data Variables.
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There are many different metrics to consider, but maybe the first question to ask yourself is – did you talk to the business users?

The results of these discussions should be captured and used to formulate business rules.  These business rules will hold the clue to what data variables (or metrics) are most important to monitor/track/graph.

What data variable(s) are useful to determine when a customer record should be classified as active or inactive? August 25, 2007

Posted by Peter Benza in Data Analysis, Data Management, Data Metrics, Data Mining, Data Processes, Data Research, Data Variables.
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Data quality and plotting customer address data on a map August 19, 2007

Posted by Peter Benza in Data Analysis, Data Hygiene, Data Integration, Data Metrics, Data Profiling, Data Quality, Data Tools.
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Consider the insights and knowledge your organization will gain about the quality of its customer name/address data prior to centralizing all the desparate data sources into one location.  Here is a actual slide deck I prepared a few years ago using the output from my analysis to illustrate how maps and data profiling can assist in assessing data quality. 

What is a good approach to start measuring data currency as it relates to my organization? August 13, 2007

Posted by Peter Benza in Data Currency, Data Governance, Data Metrics, Data Sources, Data Synchronization.
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Frequency is a good start.  Compile the lag time between updates representing all the different “content” (data) that accompanies each software application across your organization both internally generated and externally supplied by third parties. 

Compare this to your overall file build process, make adjustments, and update your data synchronization standards to reflect any new data sources.  Warning: Be sure to consider the impact these changes may have on other departments, especially marketing.