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Documents related to » data dictionary definition


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 DICTIONARY DEFINITION: Six Steps to Manage Data Quality with SQL Server Integration Services Six Steps to Manage Data Quality with SQL Server Integration Services Source: Melissa Data Document Type: White Paper Description: 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
9/9/2009 2:32:00 PM

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.

DATA DICTIONARY DEFINITION: Success Factors to Cleansing Data Four Critical Success Factors to Cleansing Data Source: PM ATLAS Business Group, LLC Document Type: White Paper Description: 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. Four Critical Success Factors to Cleansing Data
1/14/2006 9:29:00 AM

Achieving a Successful Data Migration
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.

DATA DICTIONARY DEFINITION: Achieving a Successful Data Migration Achieving a Successful Data Migration Source: Informatica Document Type: White Paper Description: 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.
10/27/2006 4:30:00 PM

Data Quality: A Survival Guide for Marketing
Data Quality: a Survival Guide for Marketing. Find Free Blueprint and Other Solutions to Define Your Project In Relation To Data Quality. The success of direct marketing, measured in terms of qualified leads that generate sales, depends on accurately identifying prospects. Ensuring data accuracy and data quality can be a big challenge if you have up to 10 million prospect records in your customer relationship management (CRM) system. How can you ensure you select the right prospects? Find out how an enterprise information management (EIM) system can help.

DATA DICTIONARY DEFINITION: Data Quality: A Survival Guide for Marketing Data Quality: A Survival Guide for Marketing Source: SAP Document Type: White Paper Description: The success of direct marketing, measured in terms of qualified leads that generate sales, depends on accurately identifying prospects. Ensuring data accuracy and data quality can be a big challenge if you have up to 10 million prospect records in your customer relationship management (CRM) system. How can you ensure you select the right prospects? Find out how an
6/1/2009 5:02:00 PM

Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence
Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence. Find Free Guides and Other Solutions to Define Your Implementation In Relation To Data Integration and Business Intelligence. If you can’t see how your business is performing, how can you make the right decisions? For a company to thrive, operations and analysis must work together. The ability to access and integrate all your data sources is the start to getting the complete picture—and the key to not compromising your decision-making process. Learn more about how data integration can help consolidate your data so you can use it effectively.

DATA DICTIONARY DEFINITION: Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence Source: SAP Document Type: White Paper Description: If you can’t see how your business is performing, how can you make the right decisions? For a company to thrive, operations and analysis must work together. The ability to access and integrate all your data sources is the start to getting the complete picture—and the key to not
5/29/2009 4:28:00 PM

A CRM System Needs A Data Strategy
A customer relationship management (CRM) system is inherently valuable for supporting customer acquisition and retention by gathering data from each contact with customers and prospects. Collecting data, however, cannot be isolated from a strategy for actually using that data. Here is an overview of how to evolve the focus of a data strategy to specifically suit both the acquisition and retention phases.

DATA DICTIONARY DEFINITION: CRM System Needs A Data Strategy A CRM System Needs A Data Strategy David McNamara - July 3, 2003 Read Comments Introduction An underutilized customer relationship management (CRM) system - or one that cannot match its owner s expectations - will reflect poorly on both the vendor who sold it and the IT manager who authorized the purchase and installed it. Both, however, can help successfully manage such expectations (and add value to their respective roles) by wisely counseling about the strategic
7/3/2003

Data-driven Design
Creating and maintaining a successful digital experience that drives business results requires the right research insight, design, technology, and ongoing optimization. Forrester conducted an online survey of 209 digital experience professionals in the US to evaluate current practices around Web site monitoring and digital experiences. Read about the adoption, benefits, and challenges of current data-driven design processes.

DATA DICTIONARY DEFINITION:   Business Intelligence and Data Management,   Web Authoring,   Business-to-Consumer Web Sales,   Web Site Monitoring Related Industries:   Industry Independent Related Keywords:   Extractable,   Data Driven Design,   Forrester,   Analytics,   User Experience Design,   Business,   Value,   Metrics,   Website Development,   web development,   web site development tools,   web page development Source: Extractable Learn more about Extractable Readers who downloaded this white paper also
5/15/2012 1:00:00 PM

Logs: Data Warehouse Style
Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources. But where does log data fit in? Historically, log data was reported on through slow legacy applications. But with today’s log data warehouse solutions, data is centralized, allowing users to analyze and report on it with unparalleled speed and efficiency.

DATA DICTIONARY DEFINITION: Logs: Data Warehouse Style Logs: Data Warehouse Style Source: LogLogic Document Type: White Paper Description: Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources. But where does log data fit in? Historically, log data was reported on through slow legacy applications. But with today’s log data warehouse solutions, data is centralized, allowing users to analyze and report on it with unparalleled
2/8/2008 1:14:00 PM

Data Center Projects: System Planning
System planning is the Achilles’ heel of a data center physical infrastructure project. Planning mistakes can propagate through later deployment phases, resulting in delays, cost overruns, wasted time, and a compromised system. These troubles can be eliminated by viewing system planning as a data flow model, with sequenced tasks that progressively transform and refine data from initial concept to final design. Learn more.

DATA DICTIONARY DEFINITION: Data Center Projects: System Planning Data Center Projects: System Planning Source: APC by Schneider Electric Document Type: White Paper Description: System planning is the Achilles’ heel of a data center physical infrastructure project. Planning mistakes can propagate through later deployment phases, resulting in delays, cost overruns, wasted time, and a compromised system. These troubles can be eliminated by viewing system planning as a data flow model, with sequenced tasks that progressively
12/10/2008 9:35:00 AM

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 DICTIONARY DEFINITION: Data Quality Basics Data Quality Basics Source: Trillium Software Document Type: White Paper Description: 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
10/27/2006 4:30:00 PM

2012 Business Data Loss Survey results
This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now.

DATA DICTIONARY DEFINITION: 2012 Business Data Loss Survey results 2012 Business Data Loss Survey results Source: Cibecs Document Type: White Paper Description: This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now. 2012 Business Data Loss Survey results style= border-width:0px; />   comments powered by Disqus Related Topics:   Business Intelligence and Data Management Related Keywords:   data
5/30/2012 5:47:00 AM


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