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Knowledge Graphs Journey of the Connected Enterprise
Benjamin Nussbaum @bennussbaum | [email protected]
www.atomrain.com | www.graphgrid.com
More Recently…
• The understanding and discovery that comes through connec@ons is something that organiza@ons like Google (Knowledge Graph) and Facebook (Social Graph) have leveraged very well for over a decade. • We owe the rising popularity and availability of the general purpose graph databases today to the pioneers of the space, Neo Technology, the makers of Neo4j the one truly produc@on ready na@ve graph database with over 15 years of history. • Now every organiza@on can have a knowledge graph.
What are the benefits of a knowledge graph?
• You’re interac@ng with your data in its true form • Everyone can understand the data design and organiza@on • Developers get more done in less @me • Your organiza@on’s data is connected across all silos • Understanding the connec@ons is now possible
Improved Data Understanding and InteracDon
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Improved Cross-‐FuncDonal CollaboraDon
Graphs Connect Not Only Your Data But Your Whole Organiza=on
Improved Developer ProducDvity
“Complex Join” in SQL opencypher.org – Na@ve Query Language for Graphs
SQL Query vs Na@ve Graph Query (Cypher) Equivalent queries for finding the repor@ng chain within an organiza@on
Key Components of a NaDve Graph Database
• Nodes – The “things” in your data. • Rela@onships – The context of how two “things” are related. They are treated as first class en@@es. • Labels – Think of these as tags used to organize Nodes. A Node can have mul@ple labels applied to it. • Proper@es – Both Nodes and Rela=onships have Proper@es. These store a^ributes of the Node/Rela@onship.
And no paradigm has ever made more sense
• This is how the brain works – dealing with “things” and how they’re related is already how we’re wired to func@on • Solve more complex problems with less effort • Improved collabora@on between technical teams and everyone else • Flexibility to evolve your data naturally as your business changes
But a New Paradigm Requires a New Engine
Na=ve Graph Database • Op@mized for graph traversal • Rela@onships are first class • Referen@al integrity guaranteed • ACID Compliant & Transac@onal
Non-‐Na=ve Graph Database • SQL, Document, Tabular, Key Value, etc database engine with an abstrac@on layer that provides “graphy” interac@ons. • Not sympathe@c to the nature of reading and wri@ng connected data.
Choose your Engine carefully
Na=ve Graph Database • Neo4j
Non-‐Na=ve & Not Graph Databases • DataStax • Elas@c • IBM • FlockDB – edge cache • Tinkerpop – compute framework • RDF – specifica@on
The leading naDve graph database engine
• Neo4j is the world’s leading na@ve graph database • Neo4j is op@mized for connected data opera@ons • Neo4j is my go to for connected data solu@ons in the enterprise • Neo4j is used by the world’s leading enterprises • Neo4j will accelerate your knowledge graph ini@a@ves
IntegraDng with Your ExisDng Architecture
• Very low-‐risk, non-‐invasive opera@on • Create connectors for exis@ng data bases • Flow data into your knowledge graph • Real-‐@me, analy@cs, learning, understanding, etc applica@ons interact with the na@ve graph database directly • Start flowing new data directly into your knowledge graph (assuming you chose one that is ACID and guarantees referen@al integrity)
Non-‐Invasive Architecture OpDon
DataStorageandBusinessRulesExecu5on
DataMiningandAggrega5on
Applica'on
GraphDatabaseCluster
Neo4j Neo4j Neo4j
AdHocAnalysis
BulkAnaly'cInfrastructureHadoop,EDW…
DataScien'st
EndUser
DatabasesRela5onalNoSQLHadoop
Where do I go from here?
• Embrace the paradigm shih – go na@ve. • Embrace the paradigm shih – get connected. • Embrace the paradigm shih – work intui@vely. • Embrace the paradigm shih – transform your organiza@on.
Thank You! Knowledge Graphs: Journey of the Connected Enterprise
Benjamin Nussbaum @bennussbaum | [email protected]
www.atomrain.com | www.graphgrid.com