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Graph Data Analytics

Graph Data Analytics. Resolving Complexity at an Enterprise Scale. www.globalids.com. Arka Mukherjee, Ph.D. Global IDs Arka.Mukherjee@globalids.com. Topics. 1. The “Complex Data ” Context. 2. Current Challenges. 3. Governance Methodology. The “Complex Data” Context. The Big Shift.

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Graph Data Analytics

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  1. Graph Data Analytics Resolving Complexity at an Enterprise Scale www.globalids.com Arka Mukherjee, Ph.D. Global IDs Arka.Mukherjee@globalids.com

  2. Topics 1 The “Complex Data” Context 2 Current Challenges 3 Governance Methodology

  3. The “Complex Data” Context

  4. The Big Shift

  5. The cost structure is unsustainable The cost of managing information is going up exponentially.

  6. The Complexity growth is unmanageable • Complex data ecosystems • Highly dynamic • Limited traceability • Systemic Risk : Hard to measure Financial Services Institutions

  7. Question How can Enterprises handle the cost and complexity of managing complex data landscapes ?

  8. Global IDs Focus To organize enterprise data landscapes

  9. Global IDs: Product Suite

  10. Challenges

  11. The typical Financial Institution’s • #Databases > 1000 • # Tables > 200,000 • # Columns > 2,000,000

  12. Question How can we understand the relationships across 2,000,000 attributes?

  13. Converging Data Variety Data Content Structured Multi Structured Unstructured

  14. Converging Data Ecosystems Data Ecosystems SocialData Machine Data Enterprise Data

  15. Current Approaches do not Scale • Small Average Large • #Databases > 1,000 > 10,000 > 100,000

  16. A New Approach is Required

  17. 5 Utilize Graph Structures for Governance

  18. Graph Analytics : Use Cases

  19. Key Challenges • Vast diversity and volume of metadata and data • Storage and indexing of metadata to facilitate search and navigation • Understanding the connection between different pieces of metadata (Crosswalk)

  20. Utilize Graphs Structures for Storing Complex Data

  21. Use Case 1: Enterprise Metadata Search with Hadoop

  22. Use Case 2:Unstructured Data Integration

  23. Use Case 3: Cross Database Similarity Mapping

  24. Use Case 4 : Graph Analytics

  25. Demo

  26. Methodology

  27. What we do • Scan • Analyze • Map / Organize • Govern

  28. Automation

  29. 1 : Scan

  30. 2 : Semantic Analysis

  31. 3 Automate Semantic Mapping

  32. 4 Link the Data Landscape

  33. Thank You!

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