Remove Contextual Data Remove Data Quality Remove Modeling
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Enabling Integration and Interoperability Across the Grid with Knowledge Graphs

Ontotext

Current electricity data standards EU legislation, such as REMIT , charges the European Network of Transmission System Operators for Electricity (ENTSO-E) with collecting electricity market data from TSOs. TSOs must provide this data in a format from the IEC’s family of standards known as the Common Information Model (CIM).

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5 surefire ways to derail a digital transformation (without knowing it)

CIO Business Intelligence

One recent study shows that only 50% follow a product-centric operating model focusing on customer centricity and delivering delightful customer experiences. But there are common pitfalls , such as selecting the wrong KPIs , monitoring too many metrics, or not addressing poor data quality. Digital Transformation

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Five benefits of a data catalog

IBM Big Data Hub

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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Why data governance is essential for enterprise AI

IBM Big Data Hub

The recent success of artificial intelligence based large language models has pushed the market to think more ambitiously about how AI could transform many enterprise processes. However, consumers and regulators have also become increasingly concerned with the safety of both their data and the AI models themselves.

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Addressing the Elephant in the Room – Welcome to Today’s Cloudera

Cloudera

Only Cloudera has the ability to help organizations overcome the three barriers to trust in Enterprise AI: Readiness – Can you trust the safety of your proprietary data in public AI models? Reliability – Can you trust that your data quality will yield useful AI results?

Big Data 107
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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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The Importance of the Semantic Knowledge Graph

Ontotext

The growth of large language models drives a need for trusted information and capturing machine-interpretable knowledge, requiring businesses to recognize the difference between a semantic knowledge graph and one that isn’t—if they want to leverage emerging AI technologies and maintain a competitive edge.