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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.
DATA FLOW DIAGRAM WITH EXAMPLE
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9/9/2009 2:32:00 PM
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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Scalable Data Quality: A Seven-step Plan for Any Size Organization
Scalable Data Quality: a Seven-step Plan for Any Size Organization. Read IT Reports In Relation To Data Quality. Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor data quality isn’t an option—implementing a thorough data quality solution is key to your success. Find out how.
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How Companies Use Data for Competitive Advantage
Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage.
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Overall Approach to Data Quality ROI
Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI.
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The Necessity of Data Warehousing
An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.
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Master Data Management
It’s common to hear that master data management (MDM) projects are difficult to initiate. But pairing up an MDM project with another initiative already on your organization’s priority list might be easier than you think. Find out some of the basics surrounding MDM itself, including what MDM can refer to, as well as how to couple it with other projects that may already have momentum in your organization.
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6/26/2008 7:52:00 PM
Data Quality Basics
Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue.
DATA FLOW DIAGRAM WITH EXAMPLE
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10/27/2006 4:30:00 PM
Line Design in Oracle Flow Manufacturing
You have convinced upper management that flow manufacturing will enable your company to leapfrog the competition. You have appointed a flow process leader, and selected a line for your flow pilot. Now it’s time to physically perform your first line implementation. The big question is, what exactly do you need to do to make the transition from discrete to flow?
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11/29/2006 1:41:00 PM
Implementing Energy-Efficient Data Centers
But in the white paper implementing energy-efficient data centers, you'll learn how to save money by using less electricitywhether your data cente...
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6/18/2009
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