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Graph Data Analytics Arka Mukherjee, Ph.D. Global IDs Resolving Complexity at an Enterprise Scale.

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Presentation on theme: "Graph Data Analytics Arka Mukherjee, Ph.D. Global IDs Resolving Complexity at an Enterprise Scale."— Presentation transcript:

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

2 © 2013 Global IDs 2 Proprietary 11 The “Complex Data” Context Current Challenges 22 Governance Methodology 33 Topics

3 The “Complex Data” Context

4 © 2013 Global IDs 4 Proprietary The Big Shift

5 © 2013 Global IDs 5 Proprietary The cost structure is unsustainable The cost of managing information is going up exponentially.

6 © 2013 Global IDs 6 Proprietary The Complexity growth is unmanageable 1.Complex data ecosystems 2.Highly dynamic 3.Limited traceability 4.Systemic Risk : Hard to measure Financial Services Institutions

7 © 2013 Global IDs 7 Proprietary Question How can Enterprises handle the cost and complexity of managing complex data landscapes ?

8 © 2013 Global IDs 8 Proprietary Global IDs Focus To organize enterprise data landscapes

9 © 2013 Global IDs 9 Proprietary Global IDs: Product Suite

10 Challenges

11 © 2013 Global IDs 11 Proprietary The typical Financial Institution’s # Databases > 1000 # Tables > 200,000 # Columns > 2,000,000

12 © 2013 Global IDs 12 Proprietary Question How can we understand the relationships across 2,000,000 attributes?

13 © 2013 Global IDs 13 Proprietary Converging Data Variety Structured Unstructured Multi Structured Data Content

14 © 2013 Global IDs 14 Proprietary Converging Data Ecosystems Social Data Enterprise Data Machine Data Data Ecosystems

15 © 2013 Global IDs 15 Proprietary Current Approaches do not Scale # Databases > 1,000> 10,000> 100,000 Small Average Large

16 © 2013 Global IDs 16 Proprietary A New Approach is Required

17 © 2013 Global IDs 17 Proprietary 5 Utilize Graph Structures for Governance

18 Graph Analytics : Use Cases

19 © 2013 Global IDs 19 Proprietary 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 © 2013 Global IDs 20 Proprietary Utilize Graphs Structures for Storing Complex Data

21 © 2013 Global IDs 21 Proprietary Use Case 1: Enterprise Metadata Search with Hadoop

22 © 2013 Global IDs 22 Proprietary Use Case 2: Unstructured Data Integration

23 © 2013 Global IDs 23 Proprietary Use Case 3: Cross Database Similarity Mapping

24 © 2013 Global IDs 24 Proprietary Use Case 4 : Graph Analytics

25 Demo

26 Methodology

27 © 2013 Global IDs 27 Proprietary What we do 1.Scan 2.Analyze 3.Map / Organize 4.Govern

28 © 2013 Global IDs 28 Proprietary Automation

29 © 2013 Global IDs 29 Proprietary 1 : Scan

30 © 2013 Global IDs 30 Proprietary 2 : Semantic Analysis

31 © 2013 Global IDs 31 Proprietary 3 Automate Semantic Mapping

32 © 2013 Global IDs 32 Proprietary 4 Link the Data Landscape

33 Thank You!


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