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Good Data Quality Is the Secret to Successful GenAI Implementation

Dataversity

So why are many technology leaders attempting to adopt GenAI technologies before ensuring their data quality can be trusted? Reliable and consistent data is the bedrock of a successful AI strategy.

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How Data Quality Copilots Can Enhance Integrity and Quality in AI-Based Solutions

Dataversity

Public sector agencies increasingly see artificial intelligence as a way to reshape their operations and services, but first, they must have confidence in their data. Accurate information is crucial to delivering essential services, while poor data quality can have far-reaching and sometimes catastrophic consequences.

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The Cool Kids Corner: Data Quality Is Not a Fish You Can Catch 

Dataversity

This is my monthly check-in to share with you the people and ideas I encounter as a data evangelist with DATAVERSITY. This month we’re talking about Data Quality (DQ). Read last month’s column here.)

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Why Is Data Quality Still So Hard to Achieve?

Dataversity

In fact, it’s been more than three decades of innovation in this market, resulting in the development of thousands of data tools and a global data preparation tools market size that’s set […] The post Why Is Data Quality Still So Hard to Achieve? appeared first on DATAVERSITY.

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Best Practices for a Marketing Database Cleanse

Multiple industry studies confirm that regardless of industry, revenue, or company size, poor data quality is an epidemic for marketing teams. As frustrating as contact and account data management is, this is still your database – a massive asset to your organization, even if it is rife with holes and inaccurate information.

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Mind the Gap: Data Quality Is Not “Fit for Purpose”

Dataversity

Welcome to the latest edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). Last month, we explored the rise of the data product. This month, we’ll look at data quality vs. data fitness.

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RAG (Retrieval Augmented Generation) Architecture for Data Quality Assessment

Dataversity

At their core, LLMs are trained on large amounts of content and data, and the architecture […] The post RAG (Retrieval Augmented Generation) Architecture for Data Quality Assessment appeared first on DATAVERSITY. It is estimated that by 2025, 50% of digital work will be automated through these LLM models.

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Why B2B Contact and Account Data Management Is Critical to Your ROI

64% of successful data-driven marketers say improving data quality is the most challenging obstacle to achieving success. The digital age has brought about increased investment in data quality solutions. Download this eBook and gain an understanding of the impact of data management on your company’s ROI.