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Starts 1 July 2025 13:21

Ends 1 July 2025

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Connecting the Dots: Graph Analytics for Economic Sustainability

Discover how graph analytics drives economic sustainability through pattern recognition, data connections, and risk reduction strategies for more efficient and cost-effective business operations.
Data Science Conference via YouTube

Data Science Conference

2765 Courses


27 minutes

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Overview

Discover how graph analytics drives economic sustainability through pattern recognition, data connections, and risk reduction strategies for more efficient and cost-effective business operations.

Syllabus

  • Introduction to Graph Analytics
  • Overview of Graph Theory
    Importance of Graphs in Data Science
    Applications in Various Industries
  • Understanding Economic Sustainability
  • Concepts and Principles of Economic Sustainability
    Case Studies in Economic Sustainability
  • Fundamentals of Graph Analytics
  • Graph Types and Their Characteristics
    Nodes, Edges, and Properties
    Graph Data Structures and Storage
  • Graph Pattern Recognition
  • Identifying Community Structures
    Detecting Anomalies and Forewarning Systems
    Pathfinding and Shortest Path Analysis
  • Data Connections and Relationships
  • Building and Analyzing Connection Patterns
    Enhancing Data Insights through Graphs
    Leveraging Connections for Competitive Advantage
  • Risk Reduction Strategies through Graphs
  • Identifying Potential Risks in Business Operations
    Graph-Based Risk Assessment Models
    Mitigating Economic Risks with Graph Techniques
  • Graph Algorithms for Business Efficiency
  • Centrality Measures and Their Business Applications
    Clustering and Classification Techniques
    Graph-Based Optimization Strategies
  • Tools and Platforms for Graph Analytics
  • Introduction to Popular Graph Database Systems (e.g., Neo4j, Apache TinkerPop)
    Visualizing Graph Data with Software Tools
    Implementing Graph Analytics in Business Contexts
  • Case Studies and Industry Applications
  • Graph Analytics in Finance and Banking
    Sustainable Supply Chain Management using Graphs
    Energy Sector Graph Applications
  • Project Work and Practical Implementation
  • Designing a Graph Analytics Project for Economic Sustainability
    Data Collection, Processing, and Analysis
    Presentation and Peer Review of Projects
  • Future Trends in Graph Analytics and Economic Sustainability
  • Emerging Technologies and Innovations
    The Role of AI and Machine Learning in Graph Analytics
    Long-term Impact on Business and Economy
  • Course Review and Wrap-Up
  • Recap of Key Concepts and Techniques
    Discussion on Challenges and Opportunities
    Next Steps for Continued Learning and Development

Subjects

Programming