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Ai & genai

FAIR Data Principles: The Secret to Responsible AI Adoption

Discover how FAIR data principles (Findable, Accessible, Interoperable, Reusable) enable responsible AI adoption and prevent costly AI project failures. 

by Tim Padilla

Hero-image-knowledge-graph-over-data-lakehouse

Knowledge graphs & semantics

Your lakehouse isn’t AI-ready (until you add a knowledge graph)

Discover how to transform your Microsoft Fabric, Databricks, or Snowflake lakehouse into an AI-ready platform with a semantic layer using Datavid Rover.

by Balvinder Dang

semantic layer foundation for ai readiness

Knowledge graphs & semantics

How the Semantic Layer accelerates AI data readiness

Unlock AI-readiness across your enterprise. Learn how the semantic layer connects & enriches data to power agentic AI workflows - no need to start over.

by Balvinder Dang

Abstract representation of AI readiness in enterprise data systems

Ai & genai

6 considerations to make your enterprise data AI-ready

Is your enterprise data AI-ready? Use this 6-point AI readiness checklist to ensure your data is structured, contextualized, and traceable for agentic AI.

by Tim Padilla

Knowledge graphs & semantics

Past & future use cases of Knowledge Graphs and AI integration

Explore real-world transformations with knowledge graphs and AI integration across industries. Learn about the synergy between KGs & AI-LLMs!

by Sweta Kumari

Ai & genai

Gen AI and Machine Learning for business applications

Explore how emerging technologies like Generative AI and Machine Learning can transform business applications through data platforms & unified data layers.

by Tim Padilla

Data governance & quality

Data centricity and FAIR: Creating value from data

Explore the power of Data centricity and FAIR principles in maximising data value and driving innovation within organisations.

by Avinash Dixit

Marklogic

2 in a row: Datavid is Progress MarkLogic’s EMEA partner of the year!

Datavid wins EMEA Partner of the Year at Progress-MarkLogic World for the second time, recognized for data innovation and strong industry partnerships.