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TitleFile Type
Making Supply Chain Risk Management Part of Your Core Management Process
Top performing managers rely on more than plans and forecasts. To close the critical gap in planning, performance, and accountability, you'll need to adopt proactive risk management. 
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Managing Master Data for Business Performance Management: The Issues and Hyperion's Solution

This white paper defines master data management and explores the various scenarios where this issue is gaining attention both from IT and business managers. The challenge for organizations is to align business roles with responsibilities for management of specific master data domains, with IT providing the technical support for the underlying data resources and data models.

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Master Data Management: Consensus-Driven Data Definitions for Cross-Application Consistency

This TDWI Best Practices Report written by Phillip Russom, provides insightful answers and draws upon results of an Internet-based survey co-sponsored by TDWI and Teradata. The report shares fascinating results as well as recommendations and a brief review of Teradata MDM.

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Master Data Management: Powering Enterprise Business Intelligence

This white paper, by David Loshin of Knowledge Integrity, explores the challenges associated with inconsistent and unsynchronized data within an enterprise data warehouse environment.

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Mastering the Supply Chain

This whitepaper, authored by Greg Sloyer discusses the supply chain planning processes and metrics.

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Maximizing the Quantifiable Value of Enterprise Data Warehouses

This white paper provides an overview of a Continuous Value Management Process for maximizing the business value of Enterprise Data Warehouse solutions.

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Measuring Data Warehouse Return on Investment

Management wants to know the business value of the data warehouse, measured in quantitative terms, with the metrics in the form of Return on Investment (ROI). ROI refers to a few differnet ways of calculating the value of an investment which can be calculated by payback period (break-even analysis), net present value, or rate of return (yield).

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Meeting Demands for Data Warehouse Performance

Today, data warehouses must absorb new data in near-real time and provide extraordinary performance, squeezing most of the latency out of the process. Being able to provide fresher data enables the data warehouse, in turn, to participate in ongoing operational processes.

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