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Beginnt 5 June 2026 11:39

Endet 5 June 2026

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Moving Data Platforms to Knowledge Platforms - From Data Architecture to Enterprise AI

Discover how knowledge platforms and graphs revolutionize enterprise AI by transforming traditional data architectures into dynamic, context-rich knowledge systems for enhanced data utilization.
Data Science Festival via YouTube

Data Science Festival

6076 Kurse


45 minutes

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Übersicht

Discover how knowledge platforms and graphs revolutionize enterprise AI by transforming traditional data architectures into dynamic, context-rich knowledge systems for enhanced data utilization.

Lehrplan

  • Introduction to Data and Knowledge Platforms
  • Overview of Data Platforms
    Introduction to Knowledge Platforms
    The Role of Knowledge Graphs in Enterprise AI
  • Traditional Data Architectures
  • Components and Functions of Data Architectures
    Limitations of Traditional Data Infrastructures
  • Transitioning from Data to Knowledge
  • Understanding Context and Semantics in Data
    Data Integration and Interoperability
    Introducing Metadata and Ontologies
  • Building Knowledge Graphs
  • Basics of Graph Theory and Networks
    Core Technologies: RDF, OWL, SPARQL
    Design and Implementation Strategies
  • Leveraging Knowledge Platforms in Enterprise AI
  • Enhancing Data Discovery and Utilization
    Enabling Advanced Analytics and Machine Learning
  • Use Cases and Applications
  • Industry-specific Applications (Finance, Healthcare, etc.)
    Case Studies of Successful Knowledge Platform Implementations
  • Tools and Technologies
  • Overview of Current Platforms and Software
    Comparative Analysis of Popular Knowledge Graph Tools
  • Challenges and Best Practices
  • Addressing Scalability and Performance
    Ensuring Data Quality and Consistency
    Strategies for Change Management in Organizations
  • Future Trends in Knowledge Platforms and AI
  • Emerging Technologies and Innovations
    The Evolving Role of AI in Knowledge Systems
  • Course Wrap-up and Recap
  • Key Takeaways
    Future Learning Pathways and Resources

Fachgebiete

Data Science