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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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What’s Your Data Governance ROI? Here’s What to Track

Alation

In this day and age, regardless of industry, keeping data protected and its uses understood is vital. No business wants to have the PR nightmare of a data leak or personal data being used without the correct permissions. This is where successful data governance programs can act as a savior to many organizations.

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Data Maturity Models | Measure The Health Of Your Data

Anmut

This ultimately allows for more effective goal-setting, with targets determined according to both your data maturity right now and the desired stage you want to attain in the future. Why do we need data maturity models? A data maturity model helps your company measure its data and business health.

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Is the gen AI bubble due to burst? CIOs face rethink ahead

CIO Business Intelligence

Many of those gen AI projects will fail because of poor data quality, inadequate risk controls, unclear business value , or escalating costs , Gartner predicts. CIOs need to be able to articulate the business value and expected ROI of each project. For example, a gen AI virtual assistant can cost $5 million to $6.5

ROI 143
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The steep cost of a poor data management strategy

CIO Business Intelligence

Without it, businesses incur steep costs, but the downside, or costs, are often unclear because calculating data management’s return on investment (ROI), or upside, is a murky exercise. For many organizations, the real challenge is quantifying the ROI benefits of data management in terms of dollars and cents.

Strategy 113
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3 things to get right with data management for gen AI projects

CIO Business Intelligence

And Doug Shannon, automation and AI practitioner, and Gartner peer community ambassador, says the vast majority of enterprises are now focused on two categories of use cases that are most likely to deliver positive ROI. For us, it’s all part of data governance. For most organizations, data management is intrinsically tied to privacy.

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How IBM process mining unleashed new efficiencies in BoB-Cardif Life

IBM Big Data Hub

How do organizations avoid the digital risks of ‘technology misuse’ and achieve efficient innovation that ‘technology promotes production’? While optimizing management mechanisms for cost reduction, efficiency enhancement, and risk mitigation. The path of digital transformation is fraught with challenges.