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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

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Automating Model Risk Compliance: Model Development

DataRobot Blog

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. To reference SR 11-7: .

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

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3 key digital transformation priorities for 2024

CIO Business Intelligence

After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. Meanwhile, CIOs must still reduce technical debt, modernize applications, and get cloud costs under control.

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Application modernization overview

IBM Big Data Hub

Application modernization starts with assessment of current legacy applications, data and infrastructure and applying the right modernization strategy (rehost, re-platform, refactor or rebuild) to achieve the desired result. Generative AI also helps generate use cases based on code insights and functional mapping.

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The Value of Data Governance and How to Quantify It

erwin

And with many competing projects and activities vying for people’s time, it must be clear to people why choosing data governance activities will have a direct benefit to them. Usually we talk about benefits which are rather qualitative measures, but what we need for decision-making processes are values,” Pörschmann says. “We

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AI adoption accelerates as enterprise PoCs show productivity gains

CIO Business Intelligence

The cost of implementing and running AI models can be quite high, so you have to be really careful in assessing the business worthiness of AI use cases,” he says. Production is another area that benefits from AI. “At Just check to make sure you can opt out of having your data used to train the vendor’s models, he says.