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Due to the financial meltdown in the mortgage-backed securities industry, new compliance requirements will be implemented. Read this paper to find out how organizations can ensure compliance with stricter regulations and manage risk appropriately so the business does not slip into non-compliance resulting in negative publicity or punitive fines.
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What’s the truth behind the failure of many BI projects? Read this paper to learn the main factors leading to disappointment. These pitfalls are not those of new entrants to BI but have been repeated by smart and well managed companies worldwide.
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The cost and complexity of managing increasing volumes of data and content, combined with the need to provide trusted information to every user for every transaction, is driving CIOs to rethink their approach to information delivery.
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Improve planning, building, and deploying a master data management (MDM) environment. Consider an evolutionary – rather than revolutionary – approach to MDM, and examine how to use MDM with business intelligence applications and an underlying data warehousing environment to improve decision making.
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This paper analyzes the issues of conventional data warehouse design process and explains how this practice can be improved using a business-model-driven process in support of effective Business Intelligence.
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This global CIO2CIO research program was conducted for SAP, Inc. to gain insight into information management practices in various regions of the world and the research was conducted among IT professionals in the U.S., Europe and Asia.
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In this paper learn how Manufacturing Execution Systems (MES) as a part of the Product Lifecycle Management (PLM) conceptual framework are a natural collector and organizer with virtual product information.
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Master data management (MDM) improves master data correctness, consistency and accessibility. Learn about MDM, the driving forces making it an essential data management strategy and best practices for choosing and implementing a MDM solution.
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The success of a business is increasingly tied to the quality of their information. Through the Data Governance Maturity Model, organizations can identify precisely how they can create an environment that can deliver and sustain high-quality information.
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Customer Data Integration technologies can help to create a single, informative, accurate and timely view of the customer across the enterprise which can be used intelligently to achieve the banks objectives.
