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Why Data Quality is the Secret Ingredient to AI Success

insideBIGDATA

In this contributed article, engineering leader Uma Uppin emphasizes that high-quality data is fundamental to effective AI systems, as poor data quality leads to unreliable and potentially costly model outcomes.

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Rule Output Settings within a Project in IBM Knowledge Catalog: Standardising Data Quality at Scale

IBM Data Science in Practice

However, as enterprises scale, managing data quality rules becomes increasingly complex and repetitive. Recognising this challenge, IBM has introduced a significant enhancement in IBM Knowledge Catalog (IKC) version 5.1.2 : Project-Level Settings for Data Quality Rules. Any project collaborator can view the settings.

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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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Modern Data Governance: Trends for 2025

Precisely

Key Takeaways: Prioritize metadata maturity as the foundation for scalable, impactful data governance. Recognize that artificial intelligence is a data governance accelerator and a process that must be governed to monitor ethical considerations and risk.

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Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

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This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. However, as data volumes and complexity continue to grow, effective data governance becomes a critical challenge.

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Corporate Data Governance: The Cornerstone of Successful Digital Transformation

Dataversity

At the heart of this transformation lies data a critical asset that, when managed effectively, can drive innovation, enhance customer experiences, and open […] The post Corporate Data Governance: The Cornerstone of Successful Digital Transformation appeared first on DATAVERSITY.

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2025 Planning Insights: Data Quality Remains the Top Data Integrity Challenge and Priority

Precisely

Key Takeaways: Data quality is the top challenge impacting data integrity – cited as such by 64% of organizations. Data trust is impacted by data quality issues, with 67% of organizations saying they don’t completely trust their data used for decision-making.