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In the following paper, we briefly describe, and illustrate from examples, what we believe are the “Top 10” mistakes of data mining, in terms of frequency and seriousness. Most are basic, though a few are subtle. All have, when undetected, left analysts worse off than if they’d never looked at their data.
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Learn about the importance of having a data quality strategy and setting the overall goals. The six factors of data are also explained in detail and how to tie it together for implementation.
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Standardizing data management practices when developing the enterprise architecture lowers risk and increases consistency; Organizational trust in the data simplifies application development. This paper explores how a set of value-added data services can reduce operational costs, increase efficiency and improve the quality of enterprise data.
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Information management is integral to successfully maintaining a competitive advantage. The value of all your data can increase or decrease over time depending on how you manage it. Read on to learn how to gain the insights into information management you need to succeed and gain that competitive edge that is now more important than ever.
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This document delivers a step-by-step process that your organization can follow to ensure that you know who owns each data set and who should have access to that data.
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This paper outlines the rules, looks at the main threats to security compliance and highlights how a well-defined strategy, backed up by powerful technology, can provide the solution.
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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.