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Data Quality

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ALSO CALLED: Data Quality Control, Information Quality, Data Quality Assurance, 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 it. Typically this involves updating it, standardizing it, and de-duplicating records to create a single view of the data,  … 
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Data QualityIT Downloads (View All Report Types)
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IBM InfoSphere Data Architect V7.6
sponsored by IBM
TRIAL SOFTWARE: IBM InfoSphere Data Architect is a collaborative data design solution to help you discover, model, relate, and standardize diverse and distributed data assets. It supports dimensional modeling. This page contains more information about the product and access to a 30-day trial.
Posted: 20 Dec 2011 | Premiered: 20 Dec 2011

IBM

BusinessObjects Edge Series
sponsored by Business Objects
TRIAL SOFTWARE: As an independent business unit within the SAP Group, Business Objects transforms the way the world works by connecting people, information and businesses.
Posted: 01 May 2008 | Premiered: 30 Apr 2008

Business Objects

Pervasive Data Profiler v4
sponsored by Pervasive Integration
PRODUCT DEMO: Pervasive Data Profiler™ ensures data quality. Proactively audit all types of data; automate testing against changing business data quality needs and compliance regulations. Get hyper-fast, multithreaded processing of large data sets or sample data
Posted: 11 Jan 2008 | Premiered: 11 Jan 2008

Pervasive Integration
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DATA QUALITY DEFINITION (continued): …  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. forecasted that 25% of critical data within Fortune 1000 companies would continue to be inaccurate through 2007. A Gartner study says that poor quality customer data costs U.S. business an estimated $611 billion dollars a year in postage, printing, and staff overhead.Getting started with data quality … 
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