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Documents related to » data recovery


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 RECOVERY: 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

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 RECOVERY: 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

From Profit Recovery to Profit Retention
Find out how best-in class-firms strengthen accounts payable (A/P) through intelligent invoice reconciliation.

DATA RECOVERY: Implementation The Importance of Data Representation: Best Practices in Creating a Usable Report 3 Key Areas to Reduce Costs with Lean Techniques The Real Challenge of CRM: Employee Buy-In Acronym-Related White Papers: Business Intelligence (BI) |  Customer Relationship Management (CRM) |  Enterprise Resource Planning (ERP) |  Human Capital Management (HCM) |  Information Technology (IT) |  Key Performance Indicators (KPIs) |  Return on Investment (ROI) |  Software as a Service (SaaS) |  Total
8/6/2010 4:59:00 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 RECOVERY: 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

The Why of Data Collection
Data collection systems work; however, they require a investment in technology. Before the investment can be justified, we need to understand why a data collection system may be preferable to people with clipboards.

DATA RECOVERY: The Why of Data Collection The Why of Data Collection Olin Thompson - November 3, 2005 Read Comments Introduction Data collection systems work. However, they mean an investment in technology. Before we can justify that investment, we need to understand why we may want to use a data collection system in place of people with clipboards. What is data collection? In a general sense, it is the manual or automated acquisition of data. That definition has evolved to mean various automated methods of data
11/3/2005

2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unispere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses and a discussion of the results.

DATA RECOVERY: 2013 Big Data Opportunities Survey 2013 Big Data Opportunities Survey Source: SAP Document Type: White Paper Description: While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unispere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested
7/5/2013 2:25:00 PM

Poor Data Quality Means A Waste of Money
Data quality sounds like a motherhood and apple pie issue, of course we want our data to be right. However, very few enterprises get serious about it. Maybe that's because the cost of data quality is hidden. That cost can be huge.

DATA RECOVERY: Poor Data Quality Means A Waste of Money Poor Data Quality Means A Waste of Money Olin Thompson - September 23, 2003 Read Comments What Is Data Quality? When reality and the data in your system do not agree, you have a data quality problem. The system says you have 10,000 cases but you actually have 9,850. A customer s ship-to address is out of date. You have the same piece of information in two places in two applications or even two systems, but they do not agree. Many things can cause data quality
9/23/2003

Midmarket/Enterprise Backup and Recovery Buyer s Guide
Selecting the right backup and recovery solution can be complicated. Pricing and feature sets are

DATA RECOVERY:   recovery data,   data recovery,   recover files,   disk recovery,   recovery disk,   file recovery,   software recovery,   recovery software,   recovery tool,   true image,   backup for windows,   windows backup,   system recovery,   backup exec,   recover data Source: Toolbox.com Learn more about Toolbox.com Readers who downloaded this white paper also read these popular documents! Extending BI’s Reach: Anticipate Outcomes, Forecast Results, and Respond Proactively Sales Process Map
3/27/2012 8:55:00 AM

Retrofitting Data Centers
Most data centers were never designed to be data centers. Organizations are struggling to put a

DATA RECOVERY: Retrofitting Data Centers Retrofitting Data Centers Source: SharkRack Document Type: White Paper Description: Most data centers were never designed to be data centers. Organizations are struggling to put a finger in the dam to keep up with the speed of change, but budgetary restrictions are such that there is only so much a data center team can do. Learn ways to maximize your data center budget, and find out how unexpected savings in some areas can help cover expenses in other areas. Retrofitting Data
1/21/2010 12:30:00 PM

Six Misconceptions about Data Migration
A truly successful data migration project involves not only an understanding of how to migrate the data from a technical standpoint, but an understanding of how that data will be used and its importance to the operation of the enterprise.

DATA RECOVERY: Six Misconceptions about Data Migration Six Misconceptions about Data Migration Norma L. Davis - June 23, 2008 Read Comments Originally published February 4th, 2008 As organizations embark on a system implementation, one of the most important and riskiest activities is data migration—the movement of data from the old legacy system to the new system. While the selection, implementation, and operation of an enterprise application for enterprise resource planning (ERP), enterprise asset management (EAM),
6/23/2008

A Definition of Data Warehousing
There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.

DATA RECOVERY: A Definition of Data Warehousing A Definition of Data Warehousing M. Reed - August 18, 2002 Read Comments Biographical Information Bill Inmon Bill Inmon is universally recognized as the father of the data warehouse. He has over 26 years of database technology management experience and data warehouse design expertise, and has published 36 books and more than 350 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing
8/18/2002


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