Remove Data Quality Remove Data Strategy Remove Unstructured Data
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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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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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8 tips for unleashing the power of unstructured data

CIO Business Intelligence

Making the most of enterprise data is a top concern for IT leaders today. With organizations seeking to become more data-driven with business decisions, IT leaders must devise data strategies gear toward creating value from data no matter where — or in what form — it resides.

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5 tips for better business value from gen AI

CIO Business Intelligence

Successful selling has always been about volume and quality, says Jonathan Lister, COO of Vidyard. Align data strategies to unlock gen AI value for marketing initiatives Using AI to improve sales metrics is a good starting point for ensuring productivity improvements have near-term financial impact.

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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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Healthcare organizations must create a strong data foundation to fully benefit from generative AI

CIO Business Intelligence

Key elements of this foundation are data strategy, data governance, and data engineering. A healthcare payer or provider must establish a data strategy to define its vision, goals, and roadmap for the organization to manage its data. The need for generative AI data management may seem daunting.