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Connect, Enrich, Evolve: Convert Unstructured Data Silos to Knowledge Graphs

Alessandro Negro, Chief Scientist at GraphAware, discusses how to convert unstructured data silos into a graph.

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Connect, Enrich, Evolve: Convert Unstructured Data Silos to Knowledge Graphs

  1. 1. GraphAware® CONNECT. ENRICH. EVOLVE. CONVERT UNSTRUCTURED DATA SILOS TO KNOWLEDGE GRAPHS Alessandro Negro, Chief Scientist @ GraphAware @graph_aware, @AlessandroNegro
  2. 2. BUSINESS NEEDS GraphAware® → Convert Data in Actionable Knowledge Data ‣ Organisations store vast amounts of content ‣ Collect and organise past experience or mistakes ‣ Multiple distributed data silos or data sources
 Goals ‣ Do you know what your customers are going to need in 12 months’ time ‣ How are you going to provide it? ‣ Are you making the best use of information you already have in building the next generation of solutions?
  3. 3. GraphAware® BUSINESS NEEDS
  4. 4. CHALLENGES GraphAware® The challenge with knowledge are: ‣ Data and information are not consistent ‣ The amount of data ‣ Sources spread across many systems ‣ Data are generated at high speed Organisational leadership want a solution for data to be: ‣ Integrated at speed ‣ Enable knowledge workers to be more efficient, effective, and consistent
  5. 5. WHERE IS THE KNOWLEDGE? GraphAware®
  6. 6. SEARCH: 101 GraphAware®
  7. 7. SEARCH: 101 GraphAware®
  8. 8. SEARCH: INVERTED INDEX GraphAware®
  9. 9. SEARCH: INVERTED INDEX GraphAware® ← Vocabulary Inverted index →
  10. 10. WHERE IS THE KNOWLEDGE? GraphAware®
  11. 11. SEARCH: INVERTED INDEX GraphAware®
  12. 12. SEARCH: INVERTED INDEX GraphAware® Pros: ‣ Easy to implement, deploy and maintain ‣ High scalable approach related to the sharding capabilities ‣ Incredibly fast
 Cons: ‣ Tuning results is an hard task ‣ Documents are isolated (no explicit connection between them) ‣ No navigation through documents ‣ Difficult to extend ‣ Issue to change the list of synonyms ‣ Only textual search available
  13. 13. WHERE IS THE KNOWLEDGE? GraphAware®
  14. 14. GRAPH APPROACH GraphAware®
  15. 15. GRAPH APPROACH GraphAware®
  16. 16. GRAPH APPROACH GraphAware®
  17. 17. GRAPH APPROACH GraphAware®
  18. 18. GRAPH APPROACH GraphAware®
  19. 19. GRAPH APPROACH GraphAware®
  20. 20. GRAPH APPROACH GraphAware®
  21. 21. GRAPH APPROACH GraphAware®
  22. 22. GRAPH APPROACH GraphAware®
  23. 23. GRAPH APPROACH GraphAware®
  24. 24. GRAPH APPROACH GraphAware®
  25. 25. GRAPH APPROACH GraphAware®
  26. 26. GRAPH APPROACH GraphAware®
  27. 27. GRAPH APPROACH GraphAware®
  28. 28. GRAPH APPROACH GraphAware® Pros: ‣ The documents are not considered isolated ‣ Multiple, flexible and unpredictable access patterns ‣ Can be integrated with other ML approaches (i.e. recommendation) ‣ Easy to integrate with other tools ‣ Can create a Knowledge Graph ‣ Enable AI
 Cons: ‣ Textual search performance ‣ No sharding ‣ Difficult to Implement
  29. 29. KNOWLEDGE GRAPH? GraphAware® What is it? ‣ mainly describes real world entities and their interrelations, organized in a graph ‣ defines possible classes and relations of entities in a schema ‣ allows for potentially interrelating arbitrary entities with each other ‣ covers various topical domains 
 Some famous Knowledge Graphs: ‣ Google ‣ NASA ‣ Ebay ‣ Facebook ‣ Yahoo ‣ Microsoft A Knowledge Graph is the only way to manage the whole of enterprise data in full generality
  31. 31. GraphAware® “The GraphAware Knowledge Platform converts unstructured data silos to Knowledge Graph”
  33. 33. THE GRAPHAWARE KNOWLEDGE PLATFORM GraphAware® Features: ‣ Import information from your internal sources in one centralised location ‣ Enrich your data with external or internal source of knowledge ‣ Analyse information and Discover business insights using deep analysis
 How it works: ‣ Data Ingestion ‣ Smart Entity Extraction ‣ Augmented Knowledge ‣ Deep Text Analysis ‣ Distributed Processing ‣ Multiple Integration → A platform specifically designed for managing textual data
  35. 35. THE ROLE OF NEO4J GraphAware® ‣ Knowledge Graph store ‣ Single source of truth ‣ Fast access to connected data ‣ Query ‣ Merging External Data ‣ Existing Data Augmentation ‣ Scalability
  37. 37. ‣ Converting Data in actionable knowledge is a complex task ‣ It’s worth it ‣ A knowledge graph approach gives you a lot of advantages ‣ The GraphAware Knowledge Platform simplify the entire process CONCLUSION GraphAware®
  38. 38. @graph_aware