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Six Steps to Manage Data Quality with SQL Server Integration Services
Six Steps to Manage Data Quality with SQL Server Integration Services. Read IT Reports Associated with Data quality. Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.
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Achieving a Successful Data Migration. Solutions and Other Software to Delineate Your System and for Achieving a Successful Data Migration. The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.
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10/27/2006 4:30:00 PM
Optimizing Gross Margin over Continously Cleansed Data
Optimizing Gross Margin over Continously Cleansed Data.Reports and Other Software System to Use In Your System for Optimizing Gross Margin over Continously Cleansed Data. Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards are automated data cleansing, systematic management of data processes, and margin optimization. Real dollars can be reclaimed in the supply chain by making certain that every byte of product information is accurate and synchronized, internally and externally.
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6/20/2006 9:23:00 AM
Four Critical Success Factors to Cleansing Data
Four Critical Success Factors to Cleansing Data. Find Guides, Case Studies, and Other Resources Linked to Four Critical Success Factors to Cleansing Data. Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.
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1/14/2006 9:29:00 AM
Workday Tackles Big Data in the Cloud » The TEC Blog
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12-11-2012
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09-10-2012
A Road Map to Data Migration Success
The key to a successful data migration: read a Road Map to Data Migration Success, a SAP white paper. Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project teams encounter some very specific management and technical challenges. Minimizing the risk of these tricky migrations requires effective planning and scoping. Read up on the issues unique to data migration projects, and find out how to best approach them.
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1/25/2010 11:36:00 AM
Data Conversion in an ERP Environment
Converting data in any systems implementation is a high wire act. Converting data in an ERP environment should only be undertaken with a safety net, namely a well thought-out plan of execution. This article discusses the guidelines for converting data when considering manual or electronic alternatives.
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10/21/2002
Microsoft says OLE for Data Mining: Is it Bull?
Microsoft released a new version of OLE DB (Object Linking and Embedding Database, based on Microsoft’s Component Object Model or COM) which supports a proprietary data mining specification. It is purported to extend the Structured Query Language (SQL) to allow easier and faster incorporation of data mining queries into existing data warehouse solutions.
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3/28/2000
About Big Data
TEC analyst Jorge Garcia discusses the key issues surrounding big data, the different ways to manage it, and the major vendors offering big data solutions. There may not be a consensus with respect to just how big
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11/18/2011 2:08:00 PM
New Data Protection Strategies
One of the greatest challenges facing organizations is protecting corporate data. The issues that complicate data protection are compounded by increasing demand for data capacity, and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment, which impact infrastructure. IT organizations must meet these demands while maintaining flat budgets. Find out how.
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4/23/2010 5:47:00 PM
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