Identity Systems Acquisition – the Next Evolution of Data Quality
Posted by Chris Cingrani in: Data Quality > Benefits
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Continue reading "Identity Systems Acquisition – the Next Evolution of Data Quality" »
Posted by Chris Cingrani in: Data Quality > Benefits
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Continue reading "Identity Systems Acquisition – the Next Evolution of Data Quality" »
Posted by Chris Cingrani in: Data Quality > Best Practices
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Recently I spoke at a User Group Meeting on the topic “Align for Success: The critical part Data Quality plays in complex Business and IT Initiatives.” I began the discussion by polling the group to find out how many of the organizations represented had a data quality solution in place. The response to the question was mixed, with approximately half the audience indicating they either had a solution or were considering one, while the other half indicated they weren’t currently considering data quality (or the person was unaware of any data quality initiatives). Although this was a very unscientific survey, it set the tone for my presentation, as I attempted to explain the concept of a data quality maturity model. By understanding where an organization is today from the standpoint of the model, management can begin to develop plans as to where they want to end up both in the short and long term.
Continue reading "Data Quality Maturity Model – How Does Your Organization Rate?" »
Posted by Informatica in: Data Quality
Dr. Claudia Imhoff, President & Founder, Intelligent Solutions and Ed Lindsey, National Product Specialist, Informatica answer some questions that were raised during our recent web seminar. If you missed the web seminar, you can listen to it by clicking the following link:
Q: Who in the organization should be responsible for data quality? And who should sign off on the scope document?
Posted by Informatica in: Data Quality
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Today I am doing a webcast with Informatica on just this topic. The answer lies in your ability to demonstrate the true state of the data -- "seeing" the problems by performing data profiling on your data. Nothing says "Houston, we have a problem" more than viewing the profiling results. It will make believers out of the most difficult people!
I hope you enjoy the presentation.
Update: Questions and answers from this event can be in the following post - Profile Early, Profile Often
Posted by Chris Cingrani in: Data Quality > Governance / Stewardship
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Continue reading "Rome Wasn’t Built in a Day and Neither is a Data Governance Initiative" »
Posted by Tom Golden in: Data Quality > Benefits ; Data Quality > Best Practices ; Data Quality ; Data Quality > Technology
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The Webopedia.com CDI definition went: “Short for Customer Data Integration, it is the combination of the technology, processes, and services needed to create and maintain an accurate, timely and complete view of the customer across multiple channels, business lines, and, potentially, enterprises, where there are multiple sources of customer data in multiple application systems and databases.”
A bit long winded perhaps, but the three words that shone out at me through the glare of the florescent lights in San Francisco airport were “accurate, timely and complete”; all data quality issues. Despite this, few if any of the Customer Data Integration (CDI) vendors in the market today have truly addressed the data quality issues in their CDI solutions. And anyone who has gone down the route of developing their own custom-built CDI application will be all too familiar with the data quality demands involved.
Continue reading "You can’t have CDI without Data Quality" »
Posted by Larry English in: Data Quality ; Data Quality > Vertical Solutions
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This blog is the first of a series of three blogs on the critical quality characteristics (or measures) of information quality required to achieve Total Information Quality Management.
1. Information Product Specification data quality
2. Data content quality
3. Information presentation quality
What constitutes the “Information Product Specifications” data?
• Information standards
• Data names
• Data definitions
• Attribute valid value set or range of values
• Value format for structured attributes (VIN, SSN, Product Codes)
• Business rule specifications of constraints on data
• Information Steward accountable for data definition quality
Continue reading "IQ and Information Product Specifications Quality" »
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