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Are enterprises ready to adopt AI at scale?

CIO Business Intelligence

The path to achieving AI at scale is paved with myriad challenges: data quality and availability, deployment, and integration with existing systems among them. A data mesh is a set of best practices for managing data in a decentralized organization, allowing for easy sharing of data products and a self-service approach to data management.

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Unbundling the Graph in GraphRAG

O'Reilly on Data

Then connect the graph nodes and relations extracted from unstructured data sources, reusing the results of entity resolution to disambiguate terms within the domain context. Chunk your documents from unstructured data sources, as usual in GraphRAG. Link the extracted entities to their respective text chunks.

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Unlocking the full potential of enterprise AI

CIO Business Intelligence

Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1]

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Data distilleries: CIOs turn to new efficient enterprise data platforms

CIO Business Intelligence

In today’s data-driven world, large enterprises are aware of the immense opportunities that data and analytics present. Yet, the true value of these initiatives is in their potential to revolutionize how data is managed and utilized across the enterprise.

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The Role of Enterprise Knowledge Graphs in LLMs

Analytics Vidhya

They can understand and generate human language and produce content like text, imagery, audio, and synthetic data, making them highly versatile in various applications.

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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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Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

In many cases, this eliminates the need for specialized teams, extensive data labeling, and complex machine-learning pipelines. The extensive pre-trained knowledge of the LLMs enables them to effectively process and interpret even unstructured data.

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