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The importance of data ingestion and integration for enterprise AI

IBM Big Data Hub

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

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Why data governance is essential for enterprise AI

IBM Big Data Hub

Data governance for LLMs The best breakdown of LLM architecture I’ve seen comes from this article by a16z (image below). It is supported by querying, governance and open data formats to access and share data across the hybrid cloud. A strong data foundation is critical for the success of AI implementations.

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Constructing A Digital Transformation Strategy: Putting the Data in Digital Transformation

erwin

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. erwin Data Literacy provides self-service, role-based, contextual data views.

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Knowledge Graphs for Retail – Connecting People, Products and Platforms

Ontotext

It’s best to think of knowledge graphs as a rich network of meaningfully connected data about products, people, locations, personal preferences, suppliers, etc. As such, they incorporate information and develop inferences from otherwise disconnected systems to enable efficient insights and operations based on contextualized data.

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If Curiosity Cabinets Were Knowledge Graphs

Ontotext

By promoting a method of representation using a contextual data framework (one which provides the context in which a thing, place, person, group, event or period is recorded), rather than using existing documentation standards, a richer semantic representation could be used more relevant to a wider range of audiences and users.

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Five benefits of a data catalog

IBM Big Data Hub

With a data catalog, Alex can discover data assets she may have never found otherwise. An enterprise data catalog automates the process of contextualizing data assets by using: Business metadata to describe an asset’s content and purpose. A business glossary to explain the business terms used within a data asset.