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Why data quality drives AI success

CIO Business Intelligence

Organizations must prioritize strong data foundations to ensure that their AI systems are producing trustworthy, actionable insights. In Session 2 of our Analytics AI-ssentials webinar series , Zeba Hasan, Customer Engineer at Google Cloud, shared valuable insights on why data quality is key to unlocking the full potential of AI.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

Today, we are pleased to announce that Amazon DataZone is now able to present data quality information for data assets. Other organizations monitor the quality of their data through third-party solutions. Additionally, Amazon DataZone now offers APIs for importing data quality scores from external systems.

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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

As someone deeply involved in shaping data strategy, governance and analytics for organizations, Im constantly working on everything from defining data vision to building high-performing data teams. My work centers around enabling businesses to leverage data for better decision-making and driving impactful change.

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Digital transformation 2025: What’s in, what’s out

CIO Business Intelligence

Defining policies and other AI governance was a priority at many organizations trying to channel how employees used copilots while protecting sensitive data from leaking to public LLMs. For AI to deliver safe and reliable results, data teams must classify data properly before feeding it to those hungry LLMs.

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A Data Governance Self-Assessment Test

TDAN

The purpose of this article is to provide a model to conduct a self-assessment of your organization’s data environment when preparing to build your Data Governance program. Take the […].

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The Journey to DataOps Success: Key Takeaways from Transformation Trailblazers

DataKitchen

In early April 2021, DataKItchen sat down with Jonathan Hodges, VP Data Management & Analytics, at Workiva ; Chuck Smith, VP of R&D Data Strategy at GlaxoSmithKline (GSK) ; and Chris Bergh, CEO and Head Chef at DataKitchen, to find out about their enterprise DataOps transformation journey, including key successes and lessons learned.