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| IT Management > Systems Operations > Data Management > |
Data Quality
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ALSO CALLED: Data Quality Control, Information Quality, Data Quality Assurance, and Data Content Quality
DEFINITION: Data quality is the reliability and effectiveness of data, particularly in a data warehouse. Data quality assurance (DQA) is the process of verifying the reliability and effectiveness of data. Maintaining data quality requires going through the data periodically and scrubbing
Definition continues below.
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IT Risk the Impact of Data Quality in Change & Configuration Management
sponsored by Tideway Systems
WEBCAST: Posted: 10 May 2008 | When: Available On Demand
SUMMARY:
In this webcast you will learn how business competitiveness requires a predictable and reliable IT service and this cannot be achieved by relying on a "cottage industry" approach as tribal knowledge is no longer enough.
 
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Data Profiling: Underpinning Data Quality Management
sponsored by Pitney Bowes Group 1 Software
WHITE PAPER: Posted: 09 May 2008 | Published: 01 Jan 2007
SUMMARY:
Data Profiling delivers a deeper and broader insight in a fraction of the time required by traditional approaches to data analysis.
 
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Informatica Data Migration Guidebook: Research, Best Practices and ROI
sponsored by Informatica
WHITE PAPER: Posted: 09 May 2008 | Published: 01 Jan 2008
SUMMARY:
This guidebook is designed to help companies identify and understand the benefits of using Informatica for data migration and ways to maximize those benefits.
 
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The New Information Agenda: Do You Have One?
sponsored by IBM
WHITE PAPER: Posted: 09 May 2008 | Published: 01 Jan 2008
SUMMARY:
The cost and complexity of managing increasing volumes of data and content, combined with the need to provide trusted information to every user for every transaction, is driving CIOs to rethink their approach to information delivery.
 
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Techniques and Tools for Data Quality Management
sponsored by Identity Systems
WEBCAST: Posted: 08 May 2008 | When: 28 May 2008, 14:00 EDT (18:00 GMT)
SUMMARY:
Data quality is evolving to focus on providing the right data in the right format, at the right time to broad, global systems. Learn best practices for data quality management and how you can implement an enterprise data quality center of excellence.
 
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Seven Practical Ways High-Volume Mailers Can Prepare for the Proposed Postal Rates and save Millions
sponsored by Pitney Bowes Group 1 Software
WHITE PAPER: Posted: 05 May 2008 | Published: 01 Jan 2007
SUMMARY:
The request for changes in postal rates proposed by the USPS® in the pending rate case look to align postal rates with the true cost of accurate, timely mail delivery. This white paper examines the seven most significant opportunities...
 
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Address Quality Hub Mail Deliverability & Postal Management
sponsored by Pitney Bowes Group 1 Software
SOFTWARE LISTING: Posted: 05 May 2008 | Published: 01 May 2008
SUMMARY:
Address Quality Hub drives optimum performance from CASS Certified address validation, correction and standardization software engines. Address Quality Hub enables you to improve the quality and timeliness of customer...
 
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Customer Data Quality Platform
sponsored by Pitney Bowes Group 1 Software
SOFTWARE LISTING: Posted: 05 May 2008 | Published: 01 May 2008
SUMMARY:
Capitalize on a more accurate view of your customers with the Pitney Bowes Group 1 Customer Data Quality Platform. This industry-leading solution makes it easy to match and consolidate data into a single, comprehensive customer record by...
 
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The Case for CRM on IBM i
sponsored by Touchtone Corporation
WHITE PAPER: Posted: 01 May 2008 | Published: 01 May 2008
SUMMARY:
IBM i and its predecessor systems have always been touchstones for system reliability, availability, serviceability and low total cost of ownership.
 
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Inovis Catalogue: Data Synchronization
sponsored by Inovis
SOFTWARE LISTING: Posted: 01 May 2008 | Published: 01 Apr 2008
SUMMARY:
Inovis Catalogue is the retail industry's leading product data synchronization application, it allows marketers, manufacturers and suppliers to share with retailers their latest product information.
 
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DATA QUALITY DEFINITION (continued):
it. Typically this involves updating it, standardizing it, and de-duplicating records to create a single view of the data, even even if it is stored in multiple disparate systems. There are many vendor applications on the market to make this job easier. Because data quality is so important from a business perspective, many large companies employ a data steward to be in charge of data quality. In spite of this, Gartner Inc. reports that 25% of critical data within Fortune 1000 companies will
Data Quality definition sponsored by SearchDataManagement.com, powered by WhatIs.com an online computer dictionary
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