Oops! The input is malformed! Data Warehousing White Papers - Bill Inmon - BeyeNETWORK China


White Papers

 

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Title Popularity * Date
Delivering Data in an Operational Business Intelligence Environment Summary
An operational BI environment presents new and challenging success criteria for data delivery platforms. Entrinsik Informer Web Reporting addresses many of these critical design elements.

Topics: Data Warehousing, Business Intelligence, Data Acquisition and Delivery, Data Marts, Data Modeling and Design, Enterprise Information Integration (EII)
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05-20-2010
Customer Centricity, Master Data and the 360-Degree View Summary
When reviewing the popular literature on customer data integration and master data management, a frequently recurring business driver is the ability to establish a 360-degree view of the customer. This concept has turned into the holy grail of comprehensive customer intelligence. This paper provides questions that should be considered and reviewed during any project designed to deliver a 360-degree view. By using these questions for preliminary guidance, one may clearly articulate where the business can derive value, determine performance metrics and thresholds, and improve the chances of success. The paper then explores how information sharing and identity resolution combine to show the connection between MDM and enterprise customer centricity.

Topics: Information Quality (IQ), CRM, Data Quality, Data Warehousing, Master Data Management (MDM), Customer Data Integration
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05-06-2010
De-Risking Data Migration: The Case for Data Quality Technology Summary
This white paper by Dylan Jones provides practical advice that will help the reader understand the pivotal role data quality technology must play in a data migration. Jones describes five distinct implementations of data quality technology in detail, each one providing clear evidence for the need to - and the benefits of - adopting the right data quality approach in data migration projects.

Topics: Data Warehousing, Data Quality, Information Quality (IQ), Data Migration, Data Management
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05-06-2010
Data Migration for Project Leaders Summary
The project leader can play a critical role in ensuring a successful data migration. This guidebook by Dylan Jones of Data Quality Pro examines exactly what responsibilities and activities project leaders should fulfill and supplies details for these responsibilities, including sections on essential activities such as planning, forecasting, risk management, team selection, communication and collaboration.

Topics: Data Warehousing, Information Management, Data Quality, Data Migration, Data Management
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05-06-2010
Lessons Learned: Survey of Financial Services Companies Uncovers Data Governance Trends Summary
DataFlux conducted a survey to understand data management trends in the financial services industry. This white paper is based on that survey and examines how this industry is approaching managing its data, the breadth and depth of data governance in this sector, what motivates data management strategies, and what kind of rules the industry thinks should be introduced in the future to promote success.

Topics: Data Governance, Information Management, Data Management
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05-06-2010
Finding an Upside in the Downturn with Data Quality Summary
The current macroeconomic malaise means organizations in almost every sector are finding it tough. Although companies are relying even more on IT systems to run their businesses in a leaner and meaner fashion, new IT investments are invariably impacted as well. CIOs are left scratching their heads on how to sustain and fund important information management projects such as master data management (MDM) and data quality. This paper from Ovum, a leading research firm in technology, telecommunications and other business sectors, describes why a rigorous data quality program is now a business imperative rather than a luxury.

Topics: Information Quality (IQ), Information Management, Data Quality, Master Data Management (MDM), Data Governance, Data Management
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05-06-2010
A Guide to the Value of Reliable Data in Insurance Summary
How critical is reliable data to the insurance industry? Insurance companies must attract the right customers, price correctly, write the right business, decline high-risk business, mitigate risk and reserve correctly. They must also maintain positive cash flow, manage outstanding claims and get the best re-insurance deals all the while minimizing operating expenses. If unreliable data is flowing through the organization, the impact on the core insurance operational and analytical processes can be catastrophic. This white paper from industry thought leader Mike Ferguson looks at the importance of reliable data to the insurance industry, focusing on the impact of poor data. He discusses how an enterprise data quality approach can help get you back control of your data.

Topics: Information Quality (IQ), Data Quality, Data Warehousing, Enterprise Information Management (EIM), Data Management
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05-06-2010
DB2 Warehouse Performance Monitoring and Optimization Summary
This paper discusses IBM's solution to manage the complete lifecycle of BI and data warehousing with comprehensive monitoring and optimization.

Topics: Data Warehousing, Business Intelligence
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12-06-2007
Integrating Medical Data Summary
Medical and healthcare data has always been troublesome when it comes to integration and analysis.

Topics: Data Integration
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11-07-2005
Information Lifecycle Management for the Operational Data Store Summary
Managing the conflicting goals of better performance and operational compliance.

Topics: Data Warehousing
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03-31-2005
Information Lifecycle Management for Data Warehousing: Matching Technology to Reality Summary
An introduction to SAND searchable archive.

Topics: Data Warehousing
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03-10-2005
Data Quality In The Corporate Information Factory Summary
Companies with the most complete, accurate and reliable information will retain and gain market share.

Topics: Data Warehousing, Data Quality, Corporate Information Factory
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10-01-2004

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