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Mastering Data Governance in Insurance: Balancing Innovation with Compliance

The Data Administration Newsletter

Mastering data governance has become a critical challenge for insurers in today’s rapidly evolving insurance landscape. This blog post will explore the complexities of insurance data governance, highlighting the pitfalls and best practices.

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How to Deliver Data Quality with Data Governance: Ryan Doupe, CDO of American Fidelity, 9-Step Process

Alation

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 2: Data Definitions.

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Data Governance: The Oft-Overlooked Pillar of Strong Data Quality

Dataversity

What are the most common causes of Data Quality issues? The conventional answer to that question includes problems like inaccurate data, duplicate data, or data containing missing values.

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Mastering healthcare data governance with data lineage

IBM Journey to AI blog

The healthcare industry faces arguably the highest stakes when it comes to data governance. For starters, healthcare organizations constantly encounter vast (and ever-increasing) amounts of highly regulated personal data. healthcare, managing the accuracy, quality and integrity of data is the focus of data governance.

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Understanding Data Governance

IBM Journey to AI blog

If you’re in charge of managing data at your organization, you know how important it is to have a system in place for ensuring that your data is accurate, up-to-date, and secure. That’s where data governance comes in. What exactly is data governance and why is it so important?

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Data Errors in Financial Services: Addressing the Real Cost of Poor Data Quality

The Data Administration Newsletter

Data quality issues continue to plague financial services organizations, resulting in costly fines, operational inefficiencies, and damage to reputations. Key Examples of Data Quality Failures — […]

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New Tools, New Tech, Same Roadblocks: Data Governance in the Age of AI

Dataversity

Despite advancements in tools like ChatGPT and Google’s Gemini, fundamental issues with data governance – such as high costs, poor data quality, and security concerns – continue to hinder progress.