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Data Quality refers to the quality of data. Data are of high quality "if they are fit for their intended uses in operations, decision making and planning" (J.M. Juran). Alternatively, the data are deemed of high quality if they correctly represent the real-world construct to which they refer. These two views can often be in disagreement, even about the same set of data used for the same purpose.

Results 1 - 25 of 51 matches Sort Results By : Published Date | Title | Company name
Driving Storage Efficiency in SAN Environments
By : NetApp DWA Published Date: Feb 22, 2010
This paper outlines the considerations for architecting an efficient SAN data storage infrastructure with a focus on the NetApp solutions for increased utilization, improved performance and streamlined protection to reduce operational costs.
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NetApp DWA
Making Large UPS Systems More Efficient
By : APC by Schneider Electric Published Date: Dec 17, 2009
As energy resources become scarcer and more expensive, electrical efficiency is becoming a more important performance factor in the specification and selection of large UPS systems. There are three subtle but significant factors that can materially affect a company's cost of operating a UPS system and particularly the electrical bill. Unfortunately, the people who specify systems often fail to recognize these factors, which leads to increased costs to the owner because operational efficiencies are not correctly considered.
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APC by Schneider Electric
Energy Efficient Cooling for Data Centers: A Close-Coupled Row Solution
By : APC by Schneider Electric Published Date: Aug 21, 2009
The trend of increasing heat densities in data centers has held consistent with advances in computing technology for many years. As power density increased, it became evident that the degree of difficulty in cooling these higher power demand loads was also increasing. This article discusses the efficiency benefits of row-based cooling compared to two other common cooling architectures. Learn more today!
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APC by Schneider Electric
Unlocking the business value of information for competitive advantage
By : IBM-America Published Date: Nov 17, 2009
his executive level brochure provides the strategy behind Information on Demand (IOD), the 5 entry points to IOD and includes a summary of the 2008, information market analyst Ovum's independent evaluation of IBM's Information On Demand initiative which declared IBM to be at the "vanguard of the unified information management revolution."
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IBM-America
Customer Video: HP Pelzer
By : IBM-America Published Date: Aug 31, 2009
HP Pelzer find perfect harmony with DB2, Intel and SAP
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IBM-America
New Integrated Data Management Tools for DBAs
By : IBM-America Published Date: Aug 25, 2009
Reduce the long, after hours finger pointing through proactive performance monitoring all while facilitating collaboration and driving organizational efficiencies.
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IBM-America
Facing tough IT decisions? Get insight from midsize businesses like yours.
By : IBM-America Published Date: Aug 25, 2009
Facing tough IT decisions? Get insight from midsize businesses like yours.
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IBM-America
Overall Approach to Data Quality ROI.
By : SAP Inc. Published Date: Aug 21, 2009
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 as a whole.
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SAP Inc.
Data Quality: A Survival Guide to Marketing.
By : SAP Inc. Published Date: Aug 21, 2009
In this paper, Frank Dravis, Six Factors Consulting, discusses how even with the finest marketing organizations, the success of marketing ultimately comes down to the data.
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SAP Inc.
Tripwire and 21 CFR11: Ensuring Integrity and Trustworthiness of Electronic Clinical Data
By : Tripwire Published Date: Jun 30, 2009
Find out how a robust configuration audit and control system can enable electronic submissions and signatures, and validate electronic data, in compliance with the FDA's mandatory submission of clinical trials records.
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Tripwire
The Financial Close Optimizing Performance and Driving Financial Excellence
By : SAP Published Date: Jun 23, 2009
Learn why the requirement to close books quickly and with quality is emerging again as an important project for today's global finance function.
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SAP
Data Quality: A Survival Guide to Marketing
By : SAP Published Date: Jun 23, 2009
In this paper, Frank Dravis, Six Factors Consulting, discusses how even with the finest marketing organizations, the success of marketing ultimately comes down to the data.
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SAP
Developing A Universal Approach to Cleansing Customer and Product Data
By : SAP Published Date: Jun 23, 2009
Take a look at this review of current industry problems concerning data quality, and learn more about how companies are addressing quality problems with customer, product, and other types of corporate data. Read about products and use cases from SAP to see how vendors are supporting data cleansing.
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SAP
Overall Approach to Data Quality ROI
By : SAP Published Date: Jun 23, 2009
Learn the importance of Data Quality and the six key steps that you can take and put into process to help you realize tangible ROI on your data quality initiative.
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SAP
Extending the Reach of Your Business Intelligence Insight through a Single, Complementary Solution
By : SRC,LLC Published Date: Jun 01, 2009
To mine raw data and extract crucial insights, business decision‐makers need fast and comprehensive access to all the information stored across their enterprise, regardless of its format or location. Furthermore, that data must be organized, analyzed and visualized in ways that permit easy interpretation of market opportunities growth, shifts and trends and the business‐process changes required to address them. Gaining a true perspective on an organization’s customer base, market area or potential expansion can be a challenging task, because companies use so many relational databases, data warehouse technologies, mapping systems and ad hoc data repositories to gather and house information for a wide variety of specialized purposes.
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SRC,LLC
Profiling your Disaster Recovery Plan
By : InMage Published Date: Feb 18, 2009
It’s a fact: nearly 48 percent of first-time Disaster Recovery (DR) plan implementations fail due to inaccurate estimates of necessary resources. Due in large part to faulty methods of estimating resource requirements, such as analyzing logs generated by tape backup software, organizations come to conclusions that are drastically wrong.
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InMage
Delivering ROI with Data Protection, Challenging Times Demand ROI Focused Vendors
By : InMage Published Date: Feb 18, 2009
During challenging economic times, companies are increasingly questioning every budget dollar they spend. Furthermore, companies are reviewing their core vendor relationships to assess which partnerships have lived up to their expectations vs. which have overpromised and under delivered.
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InMage
Taneja Group Technology Analysts Delivering True Enterprise CDT
By : InMage Published Date: Feb 18, 2009
The concept of Continuous Data Technologies (CDT) emerged on the scene two years ago, and is now transforming the data storage industry. Nearly every major storage vendor has one or more CDT products in their offering roadmap, in addition to a vital community of emerging vendors who are the true innovators in this space.
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InMage
Enterprise Strategy Group Replication Methodologies and Applications
By : InMage Published Date: Feb 18, 2009
Replication has become a catchall phrase that while gaining in allure is also gaining in confusion – especially in the mid-tier where data is just as important as the high-end, but IT staffing and budgets are far more limited. IT people as well as vendors have a tendency to lump all data movement functions together as replication, regardless of the method or the reason.
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InMage
5 Important Steps to Successful Performance Management & BI An Analyst's Perspective
By : IBM-America Published Date: Feb 02, 2009
Sign up for the webcast and you will learn: The strategic benefits of a robust information infrastructure for performance management, How to take immediate action if your operating reporting has data latency challenges, How to drive broader adoption in the business by addressing critical data challenges, Why the combination of IBM and Cognos, an IBM company, accelerates the delivery and quality of the information needed to drive business performance.
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IBM-America
Needing to meet compliance requirements for Government Connect?
By : LogLogic, Inc. Published Date: Dec 10, 2008
Need to become compliant and participate in GSCx and also follow the Mandatory Requirement 21 detailed in the “Data Handling procedures in Government final report?”  These requirements detail the log and forensic policy requirements that must be met by government entities.  Many institutions have legacy systems that need to interconnect to a compliance solution, and your chosen solution can make the difference between overspending or missing compliance deadlines.
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LogLogic, Inc.
Scalable Data Quality: A Seven Step Plan for Any Organization
By : Melissa Data Published Date: Nov 18, 2008
This white paper describes the seven steps you need to develop a plan for data quality – one that scales to your growing business needs.
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Melissa Data
The Real Cost of Bad Data: The 1-10-100
By : Melissa Data Published Date: Nov 18, 2008
What are the long-term costs of bad data? This white paper gives you the answers and tells you how to fix it.
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Melissa Data
Is a Data Quality Web Service the Right Solution for You?
By : Melissa Data Published Date: Nov 18, 2008
Learn what a Web Service is and how it works, the advantages of using a Data Quality Web Service, the technology assessment for implementation, and several case studies (Saab and other real world case studies) to demonstrate real life successes.
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Melissa Data
Exclusive Interview: John Nydam & Tom Brennan
By : Melissa Data Published Date: Nov 18, 2008
Tom Brennan and John Nydam explain the Melissa Data and Stalworth partnership, discuss the business problems caused by bad data, and describe how DQ*Plus provides a complete data quality solution for enterprise applications and commercial databases.
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Melissa Data
 
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