Remove Data Quality Remove Enterprise Remove Structured Data
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When is data too clean to be useful for enterprise AI?

CIO Business Intelligence

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

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Unbundling the Graph in GraphRAG

O'Reilly on Data

Entity resolution merges the entities which appear consistently across two or more structured data sources, while preserving evidence decisions. A generalized, unbundled workflow A more accountable approach to GraphRAG is to unbundle the process of knowledge graph construction, paying special attention to data quality.

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

CIO Business Intelligence

While this process is complex and data-intensive, it relies on structured data and established statistical methods. This is where an LLM could become invaluable, providing the ability to analyze this unstructured data and integrate it with the existing structured data models.

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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. Finally, access control policies also need to be extended to the unstructured data objects and to vector data stores.

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AI adoption accelerates as enterprise PoCs show productivity gains

CIO Business Intelligence

Some prospective projects require custom development using large language models (LLMs), but others simply require flipping a switch to turn on new AI capabilities in enterprise software. “AI In some data migration activity we’ve observed a 40% increase in various steps along the way and an increase in speed.” asks Srivastava.

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The Missing Link in Enterprise Data Governance: Metadata

Octopai

Steve needed a robust and automated metadata management solution as part of his organization’s data governance strategy. Enterprise data governance. Enterprises, such as Steve’s company, understand that they need a proper data governance strategy in place to successfully manage all the data they process.

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The Enduring Significance of Data Modeling in the Modern Data-Driven Enterprise

erwin

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. The continued federation of data in the enterprise resulted in data silos.